ICLR 2025PastMath & reasoningLarge language models
Workshop on Reasoning and Planning for Large Language Models
LLM_Reason_and_Plan
- Submission deadline
- Feb 9, 2025, 21:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (110)
Fetched from OpenReview (v2) on 2026-06-10.
A Simple Model of Inference Scaling Laws
Adaptive Self-improvement LLM Agentic System for ML Library Development
Advancing Multimodal In-Context Learning in Large Vision-Language Models with Task-aware Demonstrations
Agentic Knowledgeable Self-awareness
Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction
ARIES: Stimulating Self-Refinement of Large Language Models with and for Iterative Preference Optimization
Assessing Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks
Automating Evaluation of Creativity in LLMs with Semantic Entropy and Efficient Multi-Agent Judge
AutoToM: Automated Bayesian Inverse Planning and Model Discovery for Open-ended Theory of Mind
Benchmarking Agentic Workflow Generation
BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Can Large Language Models Reason? A Characterization via 3-SAT
Chain-of-Thought Reasoning in the Wild is not Always Faithful
Chain-of-Timeline: Enhancing LLM Zero-Shot Temporal Reasoning with SQL-Style Timeline Formalization
CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidance
Cutting Through the Noise: Boosting LLM Performance on Math Word Problems
Decoupling the components of geometric understanding
DEDUCE: DEDUCTIVE CONSISTENCY AS A FRAMEWORK TO EVALUATE LLM REASONING
DetectiveQA: Evaluating Long-Context Reasoning on Detective Novels
Disentangling Exploration of Large Language Models by Optimal Exploitation
Divide, Reweight, and Conquer: A Logit Arithmetic Approach for In-Context Learning
Diving into Self-Evolve Training for Multimodal Reasoning
EcoAct: Economic Agent Determines When to Register What Action
Enhancing Mathematical Reasoning in Language Models Through Focused Differentiation Training
ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection
Evolutionary Prompt Optimization Discovers Emergent Multimodal Reasoning Strategies in Vision-Language Models
Feedback-Aware Monte Carlo Tree Search for Efficient Information Seeking in Goal-Oriented Conversations
FLEX-TRAVELPLANNER: A BENCHMARK FOR FLEXIBLE PLANNING WITH LANGUAGE AGENTS
GRAPE: Generalizing Robot Policy via Preference Alignment
IGDA: INTERACTIVE GRAPH DISCOVERY THROUGH LARGE LANGUAGE MODEL AGENTS
Implicit Language Models are RNNs: Balancing Parallelization and Expressivity
Improving Test-Time Search for LLMs with Backtracking Against In-Context Value Verifiers
InductionBench: LLMs Fail in the Simplest Complexity Class
Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models
Language Models Use Trigonometry to Do Addition
Large Language Model-Enhanced Multi-Armed Bandits
Large Language Models to Diffusion Finetuning
Learning to Defer for Causal Discovery with Imperfect Experts
LightTransfer: Your Long-Context LLM is Secretly a Hybrid Model with Effortless Adaptation
Limits of Deep Learning: Sequence Modeling through the Lens of Complexity Theory
LLMs Are Not Good Strategists, Yet Memory-Enhanced Agency Boosts Reasoning
LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws
LM2: Large Memory Models for Long Context Reasoning
LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations
Local Look-Ahead Guidance via Verifier-in-the-Loop for Automated Theorem Proving
LogitGaze: Predicting Human Attention Using Semantic Information from Vision-Language Models
LookPlanGraph: Embodied instruction following method with VLM graph augmentation
Lost in Time: Clock and Calendar Understanding Challenges in Multimodal LLMs
MALT: Improving Reasoning with Multi-Agent LLM Training
MAS-GPT: Training LLMs To Build LLM-Based Multi-Agent Systems
MastermindEval: A Simple But Scalable Reasoning Benchmark
MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations
Meta-Prompt Optimization for LLM-Based Sequential Decision Making
MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models
MINDSTORES: Memory-Informed Neural Decision Synthesis for Task-Oriented Reinforcement in Embodied Systems
MIR-Bench: Benchmarking LLM's Long-Context Intelligence via Many-Shot In-Context Inductive Reasoning
MMCode: Benchmarking Multimodal Large Language Models in Code Generation with Visually Rich Programming Problems
Multi-Agent Verification: Scaling Test-Time Compute with Multiple Verifiers (Abridged)
Multi-modal Agent Tuning: Building a VLM-Driven Agent for Efficient Tool Usage
Multi-Turn Code Generation Through Single-Step Rewards
Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration
OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning
Offline Reinforcement Learning for LLM Multi-Step Reasoning
On the Language of Thoughts in Large Language Models
Optimizing Test-Time Compute via Meta Reinforcement Finetuning
PC-Agent: A Hierarchical Agentic Framework for Complex Task Automation on PC
PDE-Controller: LLMs for Autoformalization and Reasoning of PDEs
PHYSICS: Benchmarking Foundation Models for Problem Solving in Physics
Plan$^\ast$RAG: Efficient Test-Time Planning for Retrieval Augmented Generation
QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
Rationalization Models for Text-to-SQL
Re-Imagine: Symbolic Benchmark Synthesis for Reasoning Evaluation
Reasoning Effort and Problem Complexity: A Scaling Analysis in LLMs
Reasoning3D - Grounding and Reasoning in 3D: Fine-Grained Zero-Shot Open-Vocabulary 3D Reasoning Part Segmentation via Large Vision-Language Models
Refining Answer Distributions for Improved Large Language Model Reasoning
Reinforcement Learning in Inference Time: A Perspective from Successive Policy Iterations
Resolving Ambiguity through Personalization in LLM chat systems
Rethinking Fine-tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning
Reveal the Mystery of DPO: The Connection between DPO and RL Algorithms
Revealing chemical reasoning in LLMs through search on complex planning tasks
ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification
RL-STaR: Theoretical Analysis of Reinforcement Learning Frameworks for Self-Taught Reasoner
RuleArena: A Benchmark for LLM Rule-Guided Reasoning in Real-World Scenarios
s1: Simple test-time scaling
Scaling Flaws of Verifier-guided Search in Mathematical Reasoning
Scaling Inference-Time Search with Vision Value Model for Improved Visual Comprehension
ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use
Self-Reasoning Language Models: Unfold Hidden Reasoning Chains with Few Reasoning Catalyst
SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning
Spectral Journey: How Transformers Predict the Shortest Path
StochasTok: Improving Fine-Grained Subword Understanding in LLMs
Strategic LLM Decoding through Bayesian Games
TACO: Learning Multi-modal Models to Reason and Act with Synthetic Chains-of-Thought-and-Action
Teaching Transformers Causal Reasoning through Axiomatic Training
The in-context inductive biases of vision-language models differ across modalities
Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization
Think to Ground: Improving Spatial Reasoning in LLMs for better Visual Grounding
Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners
Towards Hierarchical Multi-Agent Workflows for Zero-Shot Prompt Optimization
Training Large Language Models to Reason in a Continuous Latent Space
TRIG-Bench: A Benchmark for Text-Rich Image Grounding
Understanding Financial Reasoning in AI: A Multimodal Benchmark and Error Learning Approach
UNDERSTANDING INFERENCE SCALING LAWS FOR MIXTURES OF LLMS
Understanding Reasoning in Thinking Language Models via Steering Vectors
Unraveling Arithmetic in Large Language Models: The Role of Algebraic Structures
Value-Based Deep RL Scales Predictably
WebWalker: Benchmarking LLMs in Web Traversal
When Debate Fails: Bias Reinforcement in Large Language Models
When More is Less: Understanding Chain-of-Thought Length in LLMs