ICML 2024 Past Large language modelsNeuroscience
ICML 2024 Workshop on LLMs and Cognition
LLMs_and_Cognition
- Submission deadline
- Jun 1, 2024, 13:30 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (62)
Fetched from OpenReview (v2) on 2026-06-10.
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A Case-based Reasoning Approach to Dynamic Few-Shot Prompting for Code Generation
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A Human-Like Reasoning Framework for Multi-Phases Planning Task with Large Language Models
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A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners
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Abstract Understanding of Core-Knowledge Concepts: Humans vs. LLMs
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An information-theoretic study of lying in LLMs
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Anthropocentric bias and the possibility of artificial cognition
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Are Large Language Models Chameleons?
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AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents
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Baba Is AI: Break the Rules to Beat the Benchmark
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Babysit A Language Model From Scratch: Interactive Language Learning by Trials and Demonstrations
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Base-Change at Prediction: Inference-Time Update of Fine-Tuned Models
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Behavioral Bias of Vision-Language Models: A Behavioral Finance View
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Can Models Learn Skill Composition from Examples?
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Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning
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Code Agents are State of The Art Software Testers
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CogErgLLM: Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics
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Cognitive Assessment of Language Models
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Cognitive Flexibility of Large Language Models
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Cognitive Modeling with Scaffolded LLMs: A Case Study of Referential Expression Generation
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Compositional Communication with LLMs and Reasoning about Chemical Structures
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Deep Content Understanding Toward Entity and Aspect Target Sentiment Analysis on Foundation Models
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Disjoint Processing Mechanisms of Hierarchical and Linear Grammars in Large Language Models
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Enhancing LLM Complex Reasoning Capability through Hyperbolic Geometry
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Fine-tuned network relies on generic representation to solve unseen cognitive task
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From Words to Worlds: Compositionality for Cognitive Architectures
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Generation constraint scaling can mitigate hallucination
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Humans Linguistically Align to their Conversational Partners, and Language Models Should Too
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Improving Self Consistency in LLMs through Probabilistic Tokenization
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In-Context Learning May Not Elicit Trustworthy Reasoning: A-Not-B Errors in Pretrained Language Models
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Is persona enough for personality? Using ChatGPT to reconstruct an agent's latent personality from simple descriptions
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Is Self-knowledge and Action Consistent or Not: Investigating Large Language Model's Personality
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Iterative Theory of Mind Assay of Multimodal AI Models
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iWISDM: Assessing instruction following in multimodal models at scale
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Large Language Models are Bad Game Theoretic Reasoners: Evaluating Performance and Bias in Two-Player Non-Zero-Sum Games
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Large Language Models are Not Inverse Thinkers Quite yet
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Large Language Models Lack Understanding of Character Composition of Words
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Learning sequence models through consolidation
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LLM Sample: part average and part ideal
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LLM-Informed Discrete Prompt Optimization
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Lost in Translation: The Algorithmic Gap Between LMs and the Brain
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Matching domain experts by training from scratch on domain knowledge
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Minimax Tree of Thoughts: Playing Two-Player Zero-Sum Sequential Games with Large Language Models
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Modeling Bilingual Disfluencies with Large Language Models
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Multi-Modal and Multi-Agent Systems Meet Rationality: A Survey
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On language models’ cognitive biases in reading time prediction
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Position Paper: Dual-System Language Models via Next-Action Prediction
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Proving that Cryptic Crossword Clue Answers are Correct
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Recursive Introspection: Teaching LLM Agents How to Self-Improve
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Self-Cognition in Large Language Models: An Exploratory Study
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SheetAgent: A Generalist Agent for Spreadsheet Reasoning and Manipulation via Large Language Models
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SkillAct: Using Skill Abstractions Improves LLM Agents
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Teaching Transformers Causal Reasoning through Axiomatic Training
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The Pupil Becomes the Master: Eye-Tracking Feedback for Tuning LLMs
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Thinking Out-of-the-Box: A Comparative Investigation of Human and LLMs in Creative Problem-Solving
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Towards Bridging Classical and Neural Computation through a Read-Eval-Print Loop
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Towards Human-AI Collaboration in Healthcare: Guided Deferral Systems with Large Language Models
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Training Energy-Efficient Large Language Models Leveraging Equilibrium Driven Bio-Plausible Neural Dynamics
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Transformers Can Do Arithmetic with the Right Embeddings
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Uncovering Latent Memories: Assessing Data Leakage and Memorization Patterns in Large Language Models
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Understanding the Cognitive Complexity in Language Elicited by Product Images
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Verbalized Machine Learning: Revisiting Machine Learning with Language Models
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What can VLMs Do for Zero-shot Embodied Task Planning?