NeurIPS 2024PastMath & reasoningLarge language models
The 4th Workshop on Mathematical Reasoning and AI
MATH-AI
Unverified seed entry. Some fields are estimates — confirm everything on the official website before planning a submission.
- Submission deadline
- Sep 16, 2024, 11:59 UTCSEED estimate of the historical deadline — verify
- Workshop day
- Dec 14, 2024
- Submission portal
- OpenReview
- Notes
- SEED DATA — name/website/date taken from the OpenReview venue record; verify remaining fields.
Accepted papers (69)
Fetched from OpenReview (v2) on 2026-06-10.
A Hessian View of Grokking in Mathematical Reasoning
ABEL: Sample Efficient Online Reinforcement Learning for Neural Theorem Proving
Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
AI-Assisted Generation of Difficult Math Questions
Attention Bias as an Inductive Bias: How to Teach Transformers Simple Arithmetic
CAFA: Coding as Auto-Formulation Can Boost Large Language Models in Solving Linear Programming Problem
CausalBench: A Comprehensive Benchmark for Evaluating Causal Reasoning Capabilities of Large Language Models
Constraint-Based Synthetic Data Generation for LLM Mathematical Reasoning
DafnyBench: A Benchmark for Formal Software Verification
Decomposing Complex Visual Comprehension into Atomic Visual Skills for Vision Language Models
DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students’ Hand-Drawn Math Images
FEABench: Evaluating Language Models on Real World Physics Reasoning Ability
Flow-DPO: Improving LLM Mathematical Reasoning through Online Multi-Agent Learning
Formal Representation and Solution of Plane Geometric Problems
Formal Theorem Proving by Rewarding LLMs to Decompose Proofs Hierarchically
Generative Verifiers: Reward Modeling as Next-Token Prediction
Genetic Curriculum Learning for Distribution Generalization on the Travelling Salesman Problem
Give me a hint: Can LLMs take a hint to solve math problems?
HARDMATH: A Benchmark Dataset for Challenging Problems in Applied Mathematics
How Transformers Reason: A Case Study on a Synthetic Propositional Logic Problem
Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for LLM Problem-Solving
InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning
Interleaving Text and Number Embeddings to Solve Mathemathics Problems
Intermediate Fine-Tuning Improves Mathematical Reasoning in Smaller Models
Lean-STaR: Learning to Interleave Thinking and Proving
Learning Elementary Cellular Automata with Transformers
Learning Mathematical Rules with Large Language Models
Library Learning Doesn’t: The Curious Case of the Single-Use “Library”
LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
Looped Transformers for Length Generalization
Machine Learning meets Algebraic Combinatorics: A Suite of Datasets to Accelerate AI for Mathematics Research
Machines and Mathematical Mutations: Using GNNs to Characterize Quiver Mutation Classes
Math for AI: On the Generalization of Learning Mathematical Problem Solving
Math2Sym: A System for Solving Elementary Problems via Large Language Models and Symbolic Solvers
MathCAMPS: Fine-grained Synthesis of Mathematical Problems From Human Curricula
MathDSL: A Domain-Specific Language for Concise Mathematical Solutions Via Program Synthesis
miniCTX: Neural Theorem Proving with (Long-)Contexts
Mining Math Conjectures from LLMs: A Pruning Approach
Models Can and Should Embrace the Communicative Nature of Human-Generated Math
NLIR: Natural Language Intermediate Representation for Mechanized Theorem Proving
Not All LLM Reasoners Are Created Equal
On Memorization of Large Language Models in Logical Reasoning
OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
Probabilistic Proof State Compression: Optimizing LLM-Guided Formal Verification
Proving Olympiad Algebraic Inequalities without Human Demonstrations
Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning
Reasoning and Tools for Forecasting
Reasoning in Reasoning: A Hierarchical Framework for Better and Faster Neural Theorem Proving
Regress, Don’t Guess – A Regression-like Loss on Number Tokens for Language Models
Repeated examples help learn arithmetic
SBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented Generation.
SBSC: Step-by-Step Coding for Improving Mathematical Olympiad Performance
Semantic Self-Consistency: Enhancing Language Model Reasoning via Semantic Weighting
Skywork-Math: Data Scaling Laws for Mathematical Reasoning in LLMs — The Story Goes On
Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling
STEM-PoM: Evaluating Language Models Math-Symbol Reasoning in Document Parsing
Structure Based Dataset on SAT Solving with Graph Neural Networks
Synchronizing Verbal Responses and Board Writing for Multimodal Math Instruction with LLMs
Synthesizing Verified Mathematical Problems
The Art of Knowing When to Stop: Analysis of Optimal Stopping in People and Machines
The Karp Dataset
Towards Faster Quantum Circuit Simulation Using Graph Decompositions, GNNs and Reinforcement Learning
Transformers Can Do Arithmetic with the Right Embeddings
Transformers to Predict the Applicability of Symbolic Integration Routines
TurtleBench: A Visual Programming Benchmark in Turtle Geometry
VerMCTS: Synthesizing Multi-Step Programs using a Verifier, a Large Language Model, and Tree Search
VinePPO: Accurate Credit Assignment in RL for LLM Mathematical Reasoning
WILT: A Multi-turn, Memorization-Robust Inductive Logic Benchmark for LLMs
Wu’s Method Boosts Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometry