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Mathematical Reasoning

Papers

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Showing 301–325 of 805 papers

TitleStatusHype
Towards Efficient and Effective Alignment of Large Language Models—0
Large Language Models for Design Structure Matrix Optimization—0
Large Language Models Have Intrinsic Meta-Cognition, but Need a Good Lens—0
A Survey on Large Language Models for Mathematical Reasoning—0
Can A Gamer Train A Mathematical Reasoning Model?Code0
VReST: Enhancing Reasoning in Large Vision-Language Models through Tree Search and Self-Reward MechanismCode0
Temporalizing Confidence: Evaluation of Chain-of-Thought Reasoning with Signal Temporal Logic—0
Can Theoretical Physics Research Benefit from Language Agents?—0
LogicPuzzleRL: Cultivating Robust Mathematical Reasoning in LLMs via Reinforcement LearningCode0
Multi-Layer GRPO: Enhancing Reasoning and Self-Correction in Large Language Models—0
Beyond Accuracy: Dissecting Mathematical Reasoning for LLMs Under Reinforcement Learning—0
ProRefine: Inference-time Prompt Refinement with Textual Feedback—0
Mathematical Reasoning for Unmanned Aerial Vehicles: A RAG-Based Approach for Complex Arithmetic ReasoningCode0
VideoMathQA: Benchmarking Mathematical Reasoning via Multimodal Understanding in Videos—0
Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning—0
Adaptive Graph Pruning for Multi-Agent CommunicationCode0
WebChoreArena: Evaluating Web Browsing Agents on Realistic Tedious Web Tasks—0
Uni-LoRA: One Vector is All You Need—0
GThinker: Towards General Multimodal Reasoning via Cue-Guided RethinkingCode0
Speculative Reward Model Boosts Decision Making Ability of LLMs Cost-EffectivelyCode0
Evaluation of LLMs for mathematical problem solving—0
RMoA: Optimizing Mixture-of-Agents through Diversity Maximization and Residual CompensationCode0
On-Policy RL with Optimal Reward Baseline—0
Scaling up the think-aloud methodCode0
Probability-Consistent Preference Optimization for Enhanced LLM ReasoningCode0
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All datasetsAIME24FrontierMathLila (IID)Lila (OOD)PGPS9KAMC23GeoQAMath500UniGeoUniGeo (PRV)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1XolverAcc94.4—Unverified
2DeepSeek-r1Acc79.8—Unverified
3Openai-o1Acc74.4—Unverified
4Openai-o1-miniAcc70—Unverified
5Search-o1Acc56.7—Unverified
6s1-32BAcc56.7—Unverified
7Openai-o1-previewAcc44.6—Unverified
8Qwen2.5-72B-InstructAcc23.3—Unverified
9Claude3.5-SonnetAcc16—Unverified
#ModelMetricClaimedVerifiedStatus
1o3Accuracy0.25—Unverified
2Gemini 1.5 Pro (002)Accuracy0.02—Unverified
3GPT-4oAccuracy0.01—Unverified
4o1-miniAccuracy0.01—Unverified
5o1-previewAccuracy0.01—Unverified
6Claude 3.5 SonnetAccuracy0.01—Unverified
#ModelMetricClaimedVerifiedStatus
1Codex (Few-Shot, 175B)Accuracy0.6—Unverified
2Bhāskara-P (Fine-tuned, 2.7B)Accuracy0.48—Unverified
3Neo-P (Fine-tuned, 2.7B)Accuracy0.39—Unverified
4GPT-3 (Few-Shot, 175B)Accuracy0.38—Unverified
5Bhāskara-A (Fine-tuned, 2.7B)Accuracy0.25—Unverified
6Neo-A (Fine-tuned, 2.7B)Accuracy0.2—Unverified
#ModelMetricClaimedVerifiedStatus
1Codex (Few-Shot, 175B)Accuracy0.59—Unverified
2Bhāskara-P (Fine-tuned, 2.7B)Accuracy0.45—Unverified
3GPT-3 (Few-Shot, 175B)Accuracy0.38—Unverified
4Bhāskara-A (Fine-tuned, 2.7B)Accuracy0.27—Unverified
5Neo-P (Fine-tuned, 2.7B)Accuracy0.24—Unverified
6Neo-A (Fine-tuned, 2.7B)Accuracy0.18—Unverified
#ModelMetricClaimedVerifiedStatus
1GOLDCompletion accuracy65.8—Unverified
2PGPSNetCompletion accuracy62.7—Unverified
3GAPSCompletion accuracy61.2—Unverified
4Inter-GPSCompletion accuracy59.8—Unverified
5GeoformerCompletion accuracy35.6—Unverified
6NGSCompletion accuracy34.1—Unverified
#ModelMetricClaimedVerifiedStatus
1QWQ-32B-previewAcc82.5—Unverified
2Math-MasterAcc82—Unverified
3Qwen2.5-Math-7B-instructAcc62.5—Unverified
#ModelMetricClaimedVerifiedStatus
1GOLDAccuracy (%)75.2—Unverified
2GAPSAccuracy (%)67.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Search-o1Acc86.4—Unverified
#ModelMetricClaimedVerifiedStatus
1GOLDAccuracy (%)98.5—Unverified
#ModelMetricClaimedVerifiedStatus
1GAPSAccuracy (%)97.5—Unverified