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Mathematical Problem-Solving

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Showing 1–50 of 106 papers

TitleStatusHype
EvoAgentX: An Automated Framework for Evolving Agentic WorkflowsCode7
LocationReasoner: Evaluating LLMs on Real-World Site Selection ReasoningCode0
TeleMath: A Benchmark for Large Language Models in Telecom Mathematical Problem Solving—0
SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM ReasoningCode1
Solving Inequality Proofs with Large Language ModelsCode1
Chain-of-Code Collapse: Reasoning Failures in LLMs via Adversarial Prompting in Code GenerationCode0
MORSE-500: A Programmatically Controllable Video Benchmark to Stress-Test Multimodal ReasoningCode1
PoLAR: Polar-Decomposed Low-Rank Adapter Representation—0
Evaluation of LLMs for mathematical problem solving—0
Decomposing Elements of Problem Solving: What "Math" Does RL Teach?Code0
Surrogate Signals from Format and Length: Reinforcement Learning for Solving Mathematical Problems without Ground Truth AnswersCode0
Error Typing for Smarter Rewards: Improving Process Reward Models with Error-Aware Hierarchical SupervisionCode0
RaDeR: Reasoning-aware Dense Retrieval ModelsCode1
Can reasoning models comprehend mathematical problems in Chinese ancient texts? An empirical study based on data from Suanjing Shishu—0
SMART: Self-Generating and Self-Validating Multi-Dimensional Assessment for LLMs' Mathematical Problem Solving—0
Towards Spoken Mathematical Reasoning: Benchmarking Speech-based Models over Multi-faceted Math Problems—0
HARDMath2: A Benchmark for Applied Mathematics Built by Students as Part of a Graduate ClassCode0
Reasoning with OmniThought: A Large CoT Dataset with Verbosity and Cognitive Difficulty Annotations—0
Is PRM Necessary? Problem-Solving RL Implicitly Induces PRM Capability in LLMs—0
PT-MoE: An Efficient Finetuning Framework for Integrating Mixture-of-Experts into Prompt TuningCode0
Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem SolvingCode2
Reasoning Models Can Be Effective Without Thinking—0
Holistic Capability Preservation: Towards Compact Yet Comprehensive Reasoning Models—0
On Vanishing Variance in Transformer Length Generalization—0
LearNAT: Learning NL2SQL with AST-guided Task Decomposition for Large Language Models—0
Exploring LLM Reasoning Through Controlled Prompt VariationsCode0
Brains vs. Bytes: Evaluating LLM Proficiency in Olympiad Mathematics—0
Entropy-Based Adaptive Weighting for Self-TrainingCode1
MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection—0
A Survey on Mathematical Reasoning and Optimization with Large Language ModelsCode0
Does Chain-of-Thought Reasoning Help Mobile GUI Agent? An Empirical StudyCode0
MathFusion: Enhancing Mathematic Problem-solving of LLM through Instruction FusionCode1
MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical ProblemsCode0
Performance Comparison of Large Language Models on Advanced Calculus Problems—0
Self-Evolved Preference Optimization for Enhancing Mathematical Reasoning in Small Language Models—0
Nexus: A Lightweight and Scalable Multi-Agent Framework for Complex Tasks AutomationCode2
SECURA: Sigmoid-Enhanced CUR Decomposition with Uninterrupted Retention and Low-Rank Adaptation in Large Language Models—0
How Do Large Language Monkeys Get Their Power (Laws)?—0
Forgotten Polygons: Multimodal Large Language Models are Shape-BlindCode1
Navigating Semantic Relations: Challenges for Language Models in Abstract Common-Sense Reasoning—0
MathFimer: Enhancing Mathematical Reasoning by Expanding Reasoning Steps through Fill-in-the-Middle Task—0
Scaling Autonomous Agents via Automatic Reward Modeling And Planning—0
STRIVE: Structured Reasoning for Self-Improvement in Claim Verification—0
Teaching LLMs According to Their Aptitude: Adaptive Reasoning for Mathematical Problem Solving—0
Code-Vision: Evaluating Multimodal LLMs Logic Understanding and Code Generation CapabilitiesCode1
Exposing Numeracy Gaps: A Benchmark to Evaluate Fundamental Numerical Abilities in Large Language ModelsCode1
Adaptive Graph of Thoughts: Test-Time Adaptive Reasoning Unifying Chain, Tree, and Graph StructuresCode2
Advancing Reasoning in Large Language Models: Promising Methods and Approaches—0
Automating Mathematical Proof Generation Using Large Language Model Agents and Knowledge Graphs—0
Token-Hungry, Yet Precise: DeepSeek R1 Highlights the Need for Multi-Step Reasoning Over Speed in MATH—0
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