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