ai-research-papers

Summaries of AI Research Papers

Prompt Engineering

• Text-driven Prompt Generation for Vision-Language Models in Federated Learning (summary | paper)
• Reverse Stable Diffusion: What prompt was used to generate this image? (summary | paper)
• Prompt-ICM: A Unified Framework towards Image Coding for Machines with Task-driven Prompts (summary | paper)
• Large Language Model Prompt Chaining for Long Legal Document Classification (summary | paper)
• Plum: Prompt Learning using Metaheuristic (summary | paper)
• Rethinking Visual Prompt Learning as Masked Visual Token Modeling (summary | paper)
• ULTRA-DP: Unifying Graph Pre-training with Multi-task Graph Dual Prompt (summary | paper)
• Prompting Hard or Hardly Prompting: Prompt Inversion for Text-to-Image Diffusion Models (summary | paper)
• SPELL: Semantic Prompt Evolution based on a LLM (summary | paper)
• Promise: Prompt-driven 3D Medical Image Segmentation Using Pretrained Image Foundation Models (summary | paper)
• Prompt Algebra for Task Composition (summary | paper)
• AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image Detectors (summary | paper)
• LMPT: Prompt Tuning with Class-Specific Embedding Loss for Long-tailed Multi-Label Visual Recognition (summary | paper)
• SD4Match: Learning to Prompt Stable Diffusion Model for Semantic Matching (summary | paper)
• Controlling Personality Style in Dialogue with Zero-Shot Prompt-Based Learning (summary | paper)
• Soft Prompt Tuning for Augmenting Dense Retrieval with Large Language Models (summary | paper)
• Multimodal Prompt Perceiver: Empower Adaptiveness, Generalizability and Fidelity for All-in-One Image Restoration (summary | paper)
• BIM-GPT: a Prompt-Based Virtual Assistant Framework for BIM Information Retrieval (summary | paper)
• Prompt-In-Prompt Learning for Universal Image Restoration (summary | paper)
• AutoHint: Automatic Prompt Optimization with Hint Generation (summary | paper)
• Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations (summary | paper)
• Prompt Middleware: Mapping Prompts for Large Language Models to UI Affordances (summary | paper)
• Prompt-Guided Transformers for End-to-End Open-Vocabulary Object Detection (summary | paper)
• Prompt-based Node Feature Extractor for Few-shot Learning on Text-Attributed Graphs (summary | paper)
• You Only Prompt Once: On the Capabilities of Prompt Learning on Large Language Models to Tackle Toxic Content (summary | paper)
• PBNR: Prompt-based News Recommender System (summary | paper)
• Generalized Graph Prompt: Toward a Unification of Pre-Training and Downstream Tasks on Graphs (summary | paper)
• HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models (summary | paper)
• PromptTTS 2: Describing and Generating Voices with Text Prompt (summary | paper)
• Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies (summary | paper)
• Negative-prompt Inversion: Fast Image Inversion for Editing with Text-guided Diffusion Models (summary | paper)
• LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression (summary | paper)
• Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers (summary | paper)
• Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting (summary | paper)
• ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design (summary | paper)
• Reflexion: Language Agents with Verbal Reinforcement Learning (summary | paper)
• A study on Prompt Design, Advantages and Limitations of ChatGPT for Deep Learning Program Repair (summary | paper)
• Prompt-Free Diffusion: Taking 'Text' out of Text-to-Image Diffusion Models (summary | paper)
• How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings (summary | paper)
• Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective (summary | paper)
• A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications (summary | paper)
• Wordflow: Social Prompt Engineering for Large Language Models (summary | paper)
• Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation (summary | paper)
• Exploring Prompt Engineering Practices in the Enterprise (summary | paper)
• ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation (summary | paper)
• MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering (summary | paper)
• Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering (summary | paper)
• Large Language Models and Prompt Engineering for Biomedical Query Focused Multi-Document Summarisation (summary | paper)
• Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies (summary | paper)
• Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPT (summary | paper)
• Prompt Engineering-assisted Malware Dynamic Analysis Using GPT-4 (summary | paper)
• Prompt-Engineering and Transformer-based Question Generation and Evaluation (summary | paper)
• PEACE: Prompt Engineering Automation for CLIPSeg Enhancement in Aerial Robotics (summary | paper)
• To be or not to be? an exploration of continuously controllable prompt engineering (summary | paper)
• A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models (summary | paper)
• Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering (summary | paper)
• Prompt Engineering a Prompt Engineer (summary | paper)
• Prompt Engineering for Healthcare: Methodologies and Applications (summary | paper)
• Large Language Models Are Human-Level Prompt Engineers (summary | paper)
• DocPrompting: Generating Code by Retrieving the Docs (summary | paper)
• PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization (summary | paper)
• LLM Guided Evolution -- The Automation of Models Advancing Models (summary | paper)
• Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review (summary | paper)
• Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery (summary | paper)
• Compositional Exemplars for In-context Learning (summary | paper)
• SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains (summary | paper)
• GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks (summary | paper)
• Scalable Prompt Generation for Semi-supervised Learning with Language Models (summary | paper)
• Guiding Large Language Models via Directional Stimulus Prompting (summary | paper)
• A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT (summary | paper)
• EvoPrompting: Language Models for Code-Level Neural Architecture Search (summary | paper)
• Dynamic Prompting: A Unified Framework for Prompt Tuning (summary | paper)
• CAMEL: Communicative Agents for 'Mind' Exploration of Large Language Model Society (summary | paper)
• Boosted Prompt Ensembles for Large Language Models (summary | paper)
• Efficient Prompting via Dynamic In-Context Learning (summary | paper)
• Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt (summary | paper)
• Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models (summary | paper)
• Hierarchical Prompting Assists Large Language Model on Web Navigation (summary | paper)
• Better Zero-Shot Reasoning with Self-Adaptive Prompting (summary | paper)
• PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documents (summary | paper)
• Exploring Lottery Prompts for Pre-trained Language Models (summary | paper)
• Graph of Thoughts: Solving Elaborate Problems with Large Language Models (summary | paper)
• From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting (summary | paper)
• Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing (summary | paper)
• A Taxonomy of Prompt Modifiers for Text-To-Image Generation (summary | paper)
• Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study (summary | paper)
• Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data (summary | paper)
• Investigating the Effectiveness of Task-Agnostic Prefix Prompt for Instruction Following (summary | paper)
• Model-tuning Via Prompts Makes NLP Models Adversarially Robust (summary | paper)
• UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation (summary | paper)
• A Comprehensive Survey on Instruction Following (summary | paper)
• Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models (summary | paper)
• Tree of Thoughts: Deliberate Problem Solving with Large Language Models (summary | paper)
• Post Hoc Explanations of Language Models Can Improve Language Models (summary | paper)
• Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting (summary | paper)
• Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation (summary | paper)
• Re-Reading Improves Reasoning in Large Language Models (summary | paper)
• Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers (summary | paper)
• LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models (summary | paper)
• Large Language Models as Analogical Reasoners (summary | paper)
• Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4 (summary | paper)
• Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic (summary | paper)
• Prompt Design and Engineering: Introduction and Advanced Methods (summary | paper)
• Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions (summary | paper)
• Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks (summary | paper)
• Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources (summary | paper)
• Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning (summary | paper)
• EntGPT: Linking Generative Large Language Models with Knowledge Bases (summary | paper)
• Chain-of-Verification Reduces Hallucination in Large Language Models (summary | paper)
• Reflexion: Language Agents with Verbal Reinforcement Learning (summary | paper)

Hallucinations

• Exploring the Relationship between LLM Hallucinations and Prompt Linguistic Nuances: Readability, Formality, and Concreteness summary | paper
• Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond (summary | paper)
• AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection (summary | paper)
• DiffusionGPT: LLM-Driven Text-to-Image Generation System (summary | paper)
• Chain-of-Verification Reduces Hallucination in Large Language Models (summary | paper)
• A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions (summary | paper)
• AutoHall: Automated Hallucination Dataset Generation for Large Language Models (summary | paper)
• Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models (summary | paper)
• Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation (summary | paper)
• Deficiency of Large Language Models in Finance: An Empirical Examination of Hallucination (summary | paper)
• Factuality of Large Language Models in the Year 2024 (summary | paper)
• Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification (summary | paper)

RAG

• Boosted Prompt Ensembles for Large Language Models (summary | paper)
• Chit-Chat or Deep Talk: Prompt Engineering for Process Mining (summary | paper)
• Prompt Engineering for Transformer-based Chemical Similarity Search Identifies Structurally Distinct Functional Analogues (summary | paper)
• Recitation-Augmented Language Models (summary | paper)
• RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval (summary | paper)
• Retrieval-Augmented Thought Process as Sequential Decision Making (summary | paper)
• Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP (summary | paper)
• Language Is Not All You Need: Aligning Perception with Language Models (summary | paper)
• Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer (summary | paper)
• Pre-Training to Learn in Context (summary | paper)
• The Web Can Be Your Oyster for Improving Large Language Models (summary | paper)
• A Step Closer to Comprehensive Answers: Constrained Multi-Stage Question Decomposition with Large Language Models (summary | paper)
• Active Retrieval Augmented Generation (summary | paper)
• KnowGPT: Knowledge Injection for Large Language Models (summary | paper)

Tutorial

• SPROUT: Authoring Programming Tutorials with Interactive Visualization of Large Language Model Generation Process (summary | paper)

Dataset Generation

• Maatphor: Automated Variant Analysis for Prompt Injection Attacks (summary | paper)
• viz2viz: Prompt-driven stylized visualization generation using a diffusion model (summary | paper)
• Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition (summary | paper)
• Language Prompt for Autonomous Driving (summary | paper)
• Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training (summary | paper)
• Text2MDT: Extracting Medical Decision Trees from Medical Texts (summary | paper)
• Analyzing Toxicity in Deep Conversations: A Reddit Case Study (summary | paper)
• GuReT: Distinguishing Guilt and Regret related Text (summary | paper)
• Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples (summary | paper)
• Mixture of Soft Prompts for Controllable Data Generation (summary | paper)
• WizardLM: Empowering Large Language Models to Follow Complex Instructions (summary | paper)

Reasoning

• An automatically discovered chain-of-thought prompt generalizes to novel models and datasets (summary | paper)
• Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL (summary | paper)
• Divide and Prompt: Chain of Thought Prompting for Text-to-SQL (summary | paper)
• Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling (summary | paper)
• LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models (summary | paper)
• Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution (summary | paper)
• Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT (summary | paper)
• Understanding prompt engineering may not require rethinking generalization (summary | paper)
• Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought (summary | paper)
• Decomposed Prompting: A Modular Approach for Solving Complex Tasks (summary | paper)
• ReAct: Synergizing Reasoning and Acting in Language Models (summary | paper)
• PAL: Program-aided Language Models (summary | paper)
• Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning (summary | paper)
• Making Large Language Models Better Reasoners with Step-Aware Verifier (summary | paper)
• Large Language Models are Zero-Shot Reasoners (summary | paper)
• Self-Consistency Improves Chain of Thought Reasoning in Language Models (summary | paper)
• Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (summary | paper)
• LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding (summary | paper)
• Inferring Properties of Graph Neural Networks (summary | paper)
• RoT: Enhancing Large Language Models with Reflection on Search Trees (summary | paper)
• STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent (summary | paper)
• Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting (summary | paper)
• GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations (summary | paper)
• On the Empirical Complexity of Reasoning and Planning in LLMs (summary | paper)
• Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning (summary | paper)
• RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models (summary | paper)
• Chain-of-Thought Reasoning is a Policy Improvement Operator (summary | paper)
• Tree of Reviews: A Tree-based Dynamic Iterative Retrieval Framework for Multi-hop Question Answering (summary | paper)
• Autonomous Tree-search Ability of Large Language Models (summary | paper)
• Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering (summary | paper)
• Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation (summary | paper)
• PathFinder: Guided Search over Multi-Step Reasoning Paths (summary | paper)
• Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models (summary | paper)
• MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems (summary | paper)
• Large Language Model Guided Tree-of-Thought (summary | paper)
• Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning (summary | paper)
• Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought (summary | paper)
• Empowering Multi-step Reasoning across Languages via Tree-of-Thoughts (summary | paper)
• Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training (summary | paper)
• Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation (summary | paper)
• Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models (summary | paper)
• Demystifying Chains, Trees, and Graphs of Thoughts (summary | paper)
• Large Language Models are reasoners with Self-Verification (summary | paper)
• Constitutional AI: Harmlessness from AI Feedback (summary | paper)
• Multimodal Chain-of-Thought Reasoning in Language Models (summary | paper)
• The Capacity for Moral Self-Correction in Large Language Models (summary | paper)
• ART: Automatic multi-step reasoning and tool-use for large language models (summary | paper)
• REFINER: Reasoning Feedback on Intermediate Representations (summary | paper)
• Why think step by step? Reasoning emerges from the locality of experience (summary | paper)
• SatLM: Satisfiability-Aided Language Models Using Declarative Prompting (summary | paper)
• Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling (summary | paper)
• What In-Context Learning "Learns" In-Context: Disentangling Task Recognition and Task Learning (summary | paper)
• TreePrompt: Learning to Compose Tree Prompts for Explainable Visual Grounding (summary | paper)
• Meta-in-context learning in large language models (summary | paper)
• Explaining Emergent In-Context Learning as Kernel Regression (summary | paper)
• Can We Edit Factual Knowledge by In-Context Learning? (summary | paper)
• Reasoning with Language Model is Planning with World Model (summary | paper)
• MultiTool-CoT: GPT-3 Can Use Multiple External Tools with Chain of Thought Prompting (summary | paper)
• Less Likely Brainstorming: Using Language Models to Generate Alternative Hypotheses (summary | paper)
• Walking Down the Memory Maze: Beyond Context Limit through Interactive Reading (summary | paper)
• Emergent Abilities of Large Language Models (summary | paper)
• Reasoning with Language Model Prompting: A Survey (summary | paper)
• Towards Reasoning in Large Language Models: A Survey (summary | paper)
• Augmented Language Models: a Survey (summary | paper)
• Natural Language Reasoning, A Survey (summary | paper)
• Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond (summary | paper)
• Post-Semantic-Thinking: A Robust Strategy to Distill Reasoning Capacity from Large Language Models (summary | paper)

Foundation Model

• Prompt Sapper: LLM-Empowered Software Engineering Infrastructure for AI-Native Services (summary | paper)
• TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (summary | paper)
• Prompt a Robot to Walk with Large Language Models (summary | paper)
• ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration (summary | paper)
• Segment Any Anomaly without Training via Hybrid Prompt Regularization (summary | paper)
• SAM on Medical Images: A Comprehensive Study on Three Prompt Modes (summary | paper)
• AI Chain on Large Language Model for Unsupervised Control Flow Graph Generation for Statically-Typed Partial Code (summary | paper)
• Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners (summary | paper)
• Universality and Limitations of Prompt Tuning (summary | paper)
• One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era (summary | paper)
• Mistral 7B: Foundation Model Research Paper Summary (summary | paper)

Fine Tuning

• FoodGPT: A Large Language Model in Food Testing Domain with Incremental Pre-training and Knowledge Graph Prompt (summary | paper)
• Image-Object-Specific Prompt Learning for Few-Shot Class-Incremental Learning (summary | paper)
• Consistency-guided Prompt Learning for Vision-Language Models (summary | paper)
• Progressive Visual Prompt Learning with Contrastive Feature Re-formation (summary | paper)
• Efficient Federated Prompt Tuning for Black-box Large Pre-trained Models (summary | paper)
• Prompt-Tuning Decision Transformer with Preference Ranking (summary | paper)
• Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering (summary | paper)
• BadCLIP: Trigger-Aware Prompt Learning for Backdoor Attacks on CLIP (summary | paper)
• TCP: Textual-based Class-aware Prompt tuning for Visual-Language Model (summary | paper)
• StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing (summary | paper)
• Jatmo: Prompt Injection Defense by Task-Specific Finetuning (summary | paper)
• Prompt-tuning latent diffusion models for inverse problems (summary | paper)
• DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning (summary | paper)
• EdgeSAM: Prompt-In-the-Loop Distillation for On-Device Deployment of SAM (summary | paper)
• Prompt Tuning of Deep Neural Networks for Speaker-adaptive Visual Speech Recognition (summary | paper)
• Visual Prompt Based Personalized Federated Learning (summary | paper)
• SpeechPrompt v2: Prompt Tuning for Speech Classification Tasks (summary | paper)
• Privacy-Preserving Prompt Tuning for Large Language Model Services (summary | paper)
• IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models (summary | paper)
• Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game (summary | paper)
• SGL-PT: A Strong Graph Learner with Graph Prompt Tuning (summary | paper)
• The Flan Collection: Designing Data and Methods for Effective Instruction Tuning (summary | paper)
• A-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting (summary | paper)
• How Does In-Context Learning Help Prompt Tuning? (summary | paper)
• Effectiveness of Data Augmentation for Parameter Efficient Tuning with Limited Data (summary | paper)
• Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning (summary | paper)
• Visual-Language Prompt Tuning with Knowledge-guided Context Optimization (summary | paper)
• Global Prompt Cell: A Portable Control Module for Effective Prompt Tuning (summary | paper)
• Focused Prefix Tuning for Controllable Text Generation (summary | paper)
• Fine-tuning Language Models for Factuality (summary | paper)
• Direct Preference Optimization: Your Language Model is Secretly a Reward Model (summary | paper)

Evaluation

• Testing LLMs on Code Generation with Varying Levels of Prompt Specificity (summary | paper)
• Soft-prompt Tuning for Large Language Models to Evaluate Bias (summary | paper)
• LLM Critics Help Catch LLM Bugs (summary | paper)
• Safeguarding Crowdsourcing Surveys from ChatGPT with Prompt Injection (summary | paper)
• Last One Standing: A Comparative Analysis of Security and Privacy of Soft Prompt Tuning, LoRA, and In-Context Learning (summary | paper)
• TopicGPT: A Prompt-based Topic Modeling Framework (summary | paper)
• Are Chatbots Ready for Privacy-Sensitive Applications? An Investigation into Input Regurgitation and Prompt-Induced Sanitization (summary | paper)
• ImageDream: Image-Prompt Multi-view Diffusion for 3D Generation (summary | paper)
• Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study (summary | paper)
• An LLM can Fool Itself: A Prompt-Based Adversarial Attack (summary | paper)
• Promptly: Using Prompt Problems to Teach Learners How to Effectively Utilize AI Code Generators (summary | paper)
• PromptAid: Prompt Exploration, Perturbation, Testing and Iteration using Visual Analytics for Large Language Models (summary | paper)
• Black-Box Prompt Optimization: Aligning Large Language Models without Model Training (summary | paper)
• State of What Art? A Call for Multi-Prompt LLM Evaluation (summary | paper)
• Prompt Cache: Modular Attention Reuse for Low-Latency Inference (summary | paper)
• Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potential (summary | paper)
• Dr ChatGPT, tell me what I want to hear: How prompt knowledge impacts health answer correctness (summary | paper)
• Improving ChatGPT Prompt for Code Generation (summary | paper)
• SAMAug: Point Prompt Augmentation for Segment Anything Model (summary | paper)
• A Novel Approach for Rapid Development Based on ChatGPT and Prompt Engineering (summary | paper)
• LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification (summary | paper)
• A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering (summary | paper)
• Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering (summary | paper)
• Prompt Engineering or Fine Tuning: An Empirical Assessment of Large Language Models in Automated Software Engineering Tasks (summary | paper)
• Design Guidelines for Prompt Engineering Text-to-Image Generative Models (summary | paper)
• Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences (summary | paper)
• Automatic Root Cause Analysis via Large Language Models for Cloud Incidents (summary | paper)
• Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines (summary | paper)
• NLPBench: Evaluating Large Language Models on Solving NLP Problems (summary | paper)
• Founder-GPT: Self-play to evaluate the Founder-Idea fit (summary | paper)
• Successive Prompting for Decomposing Complex Questions (summary | paper)
• Batch Prompting: Efficient Inference with Large Language Model APIs (summary | paper)
• Progressive Prompts: Continual Learning for Language Models (summary | paper)
• Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models (summary | paper)
• Large Language Models Can Be Easily Distracted by Irrelevant Context (summary | paper)
• Evaluating the Robustness of Discrete Prompts (summary | paper)
• Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints (summary | paper)
• Active Prompting with Chain-of-Thought for Large Language Models (summary | paper)
• Chain of Hindsight Aligns Language Models with Feedback (summary | paper)
• Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT (summary | paper)
• How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks (summary | paper)
• OpenICL: An Open-Source Framework for In-context Learning (summary | paper)
• Larger language models do in-context learning differently (summary | paper)
• CoTEVer: Chain of Thought Prompting Annotation Toolkit for Explanation Verification (summary | paper)
• Context-faithful Prompting for Large Language Models (summary | paper)
• Fairness-guided Few-shot Prompting for Large Language Models (summary | paper)
• NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference (summary | paper)
• Self-Refine: Iterative Refinement with Self-Feedback (summary | paper)
• Reflexion: Language Agents with Verbal Reinforcement Learning (summary | paper)
• Revisiting Automated Prompting: Are We Actually Doing Better? (summary | paper)
• Chain-of-Symbol Prompting Elicits Planning in Large Langauge Models (summary | paper)
• ZeroPrompt: Streaming Acoustic Encoders are Zero-Shot Masked LMs (summary | paper)
• Flatness-Aware Prompt Selection Improves Accuracy and Sample Efficiency (summary | paper)
• TELeR: A General Taxonomy of LLM Prompts for Benchmarking Complex Tasks (summary | paper)
• Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs (summary | paper)
• Interactive Natural Language Processing (summary | paper)
• Let's Verify Step by Step (summary | paper)
• Temporal evolution of depolarization and magnetic field of FRB 20201124A (summary | paper)
• A Survey on In-context Learning (summary | paper)
• A Bibliometric Review of Large Language Models Research from 2017 to 2023 (summary | paper)
• Tool Learning with Foundation Models (summary | paper)
• Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond (summary | paper)
• Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation (summary | paper)

Safety

• Does Prompt-Tuning Language Model Ensure Privacy? (summary | paper)
• Robust Safety Classifier for Large Language Models: Adversarial Prompt Shield (summary | paper)
• Adversarial Prompt Tuning for Vision-Language Models (summary | paper)
• Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information (summary | paper)
• DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer (summary | paper)
• Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration (summary | paper)
• Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models (summary | paper)
• Assessing Prompt Injection Risks in 200+ Custom GPTs (summary | paper)
• Prompt Stealing Attacks Against Text-to-Image Generation Models (summary | paper)
• PromptCARE: Prompt Copyright Protection by Watermark Injection and Verification (summary | paper)
• LLMs Can Understand Encrypted Prompt: Towards Privacy-Computing Friendly Transformers (summary | paper)
• Prompt Packer: Deceiving LLMs through Compositional Instruction with Hidden Attacks (summary | paper)
• From Prompt Injections to SQL Injection Attacks: How Protected is Your LLM-Integrated Web Application? (summary | paper)
• Prompt Injection attack against LLM-integrated Applications (summary | paper)
• Prompting GPT-3 To Be Reliable (summary | paper)
• Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods (summary | paper)
• Tree of Attacks: Jailbreaking Black-Box LLMs Automatically (summary | paper)
• On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning (summary | paper)
• Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection (summary | paper)
• CYBERSECEVAL 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models (summary | paper)
• Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification (summary | paper)
• Universal and Transferable Adversarial Attacks on Aligned Language Models (summary | paper)
• From Noise to Clarity: Unraveling the Adversarial Suffix of Large Language Model Attacks via Translation of Text Embeddings (summary | paper)
• Breaking Down the Defenses: A Comparative Survey of Attacks on Large Language Models (summary | paper)
• Many-Shot Jailbreaking (Anthropic Research) (summary | paper)
• AI Safety: Necessary, but insufficient and possibly problematic (summary | paper)