ICML 2024 accepted papers on Large language models
310 of the 2,610 papers accepted at ICML 2024 (11.9%) are on Large language models, compared with 2.4% at ICML 2023. They fall into 7 topics.
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Topics and papers
Language, safety and interpretability · 100 papers
- Improving Factuality and Reasoning in Language Models through Multiagent Debate (94 citations)
- Position: Will we run out of data? Limits of LLM scaling based on human-generated data (83 citations)
- Position: On the Possibilities of AI-Generated Text Detection (53 citations)
- A Tale of Tails: Model Collapse as a Change of Scaling Laws (39 citations)
- Magicoder: Empowering Code Generation with OSS-Instruct (26 citations)
- Copyright Traps for Large Language Models (24 citations)
- Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text (16 citations)
- In-Context Unlearning: Language Models as Few-Shot Unlearners (13 citations)
- Large Language Models are Geographically Biased (13 citations)
- Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads (13 citations)
- Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains (13 citations)
- InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models (11 citations)
and 88 more in the interactive map.
Agents, code and math · 46 papers
- Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners? (21 citations)
- SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models (17 citations)
- Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model (14 citations)
- TravelPlanner: A Benchmark for Real-World Planning with Language Agents (14 citations)
- Position: LLMs Can’t Plan, But Can Help Planning in LLM-Modulo Frameworks (11 citations)
- BetterV: Controlled Verilog Generation with Discriminative Guidance (9 citations)
- LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery (9 citations)
- Structured Chemistry Reasoning with Large Language Models (8 citations)
- AST-T5: Structure-Aware Pretraining for Code Generation and Understanding (7 citations)
- DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning (7 citations)
- OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models (7 citations)
- CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback (6 citations)
and 34 more in the interactive map.
AI and society · 42 papers
- Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews (70 citations)
- Position: TrustLLM: Trustworthiness in Large Language Models (54 citations)
- Position: Levels of AGI for Operationalizing Progress on the Path to AGI (53 citations)
- Position: Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them? (21 citations)
- Assessing Large Language Models on Climate Information (18 citations)
- Position: Mission Critical – Satellite Data is a Distinct Modality in Machine Learning (16 citations)
- The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning (13 citations)
- Position: A Safe Harbor for AI Evaluation and Red Teaming (11 citations)
- Position: AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research (5 citations)
- Position: Explain to Question not to Justify (5 citations)
- Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind (4 citations)
- AI Control: Improving Safety Despite Intentional Subversion (3 citations)
and 30 more in the interactive map.
Instruction and fine-tuning · 36 papers
- Cell2Sentence: Teaching Large Language Models the Language of Biology (62 citations)
- Accurate LoRA-Finetuning Quantization of LLMs via Information Retention (42 citations)
- Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation (19 citations)
- LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens (15 citations)
- LESS: Selecting Influential Data for Targeted Instruction Tuning (14 citations)
- Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch (13 citations)
- LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning (13 citations)
- Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models (11 citations)
- Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark (7 citations)
- CogBench: a large language model walks into a psychology lab (5 citations)
- From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning (5 citations)
- Privacy-Preserving Instructions for Aligning Large Language Models (5 citations)
and 24 more in the interactive map.
Reasoning and chain of thought · 33 papers
- Promptbreeder: Self-Referential Self-Improvement via Prompt Evolution (26 citations)
- Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models (13 citations)
- Chain of Code: Reasoning with a Language Model-Augmented Code Emulator (12 citations)
- Better & Faster Large Language Models via Multi-token Prediction (9 citations)
- EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty (6 citations)
- CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution (5 citations)
- Stay on Topic with Classifier-Free Guidance (5 citations)
- Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs (4 citations)
- EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism (4 citations)
- Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling (4 citations)
- Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws (3 citations)
- Break the Sequential Dependency of LLM Inference Using Lookahead Decoding (3 citations)
and 21 more in the interactive map.
Alignment and preferences · 32 papers
- Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference (103 citations)
- RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback (69 citations)
- Fundamental Limitations of Alignment in Large Language Models (45 citations)
- Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision (25 citations)
- ULTRAFEEDBACK: Boosting Language Models with Scaled AI Feedback (22 citations)
- Self-Rewarding Language Models (10 citations)
- Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study (8 citations)
- Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback (8 citations)
- ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models (7 citations)
- AI Alignment with Changing and Influenceable Reward Functions (6 citations)
- A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity (4 citations)
- Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation (4 citations)
and 20 more in the interactive map.
Retrieval and knowledge · 21 papers
- How Language Model Hallucinations Can Snowball (71 citations)
- Debating with More Persuasive LLMs Leads to More Truthful Answers (11 citations)
- A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules? (10 citations)
- Physics of Language Models: Part 3.1, Knowledge Storage and Extraction (7 citations)
- Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation (6 citations)
- InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining (6 citations)
- Language Models as Science Tutors (6 citations)
- MEMORYLLM: Towards Self-Updatable Large Language Models (4 citations)
- C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models (3 citations)
- Repoformer: Selective Retrieval for Repository-Level Code Completion (3 citations)
- Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models (2 citations)
- Larimar: Large Language Models with Episodic Memory Control (2 citations)
and 9 more in the interactive map.
