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Mathematical Reasoning

Papers

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Showing 701–750 of 805 papers

TitleStatusHype
MathScale: Scaling Instruction Tuning for Mathematical ReasoningCode0
Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning—0
You Need to Pay Better Attention: Rethinking the Mathematics of Attention Mechanism—0
Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models—0
MATHSENSEI: A Tool-Augmented Large Language Model for Mathematical ReasoningCode0
Reasoning in Conversation: Solving Subjective Tasks through Dialogue Simulation for Large Language Models—0
MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs—0
Look Before You Leap: Problem Elaboration Prompting Improves Mathematical Reasoning in Large Language Models—0
How Do Humans Write Code? Large Models Do It the Same Way TooCode0
Brain-Inspired Two-Stage Approach: Enhancing Mathematical Reasoning by Imitating Human Thought ProcessesCode0
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models—0
Pride and Prejudice: LLM Amplifies Self-Bias in Self-RefinementCode0
Evaluating LLMs' Mathematical Reasoning in Financial Document Question Answering—0
Reasoning over Uncertain Text by Generative Large Language ModelsCode0
Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs—0
Can Graph Descriptive Order Affect Solving Graph Problems with LLMs?—0
Beyond Lines and Circles: Unveiling the Geometric Reasoning Gap in Large Language Models—0
Large Language Models for Mathematical Reasoning: Progresses and Challenges—0
Efficient Tool Use with Chain-of-Abstraction Reasoning—0
Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems—0
GAPS: Geometry-Aware Problem Solver—0
Demystifying Chains, Trees, and Graphs of Thoughts—0
Distilling Mathematical Reasoning Capabilities into Small Language Models—0
CHAMP: A Competition-level Dataset for Fine-Grained Analyses of LLMs' Mathematical Reasoning Capabilities—0
Olapa-MCoT: Enhancing the Chinese Mathematical Reasoning Capability of LLMs—0
Knowledge Distillation of LLM for Automatic Scoring of Science Education Assessments—0
Assessing the Impact of Prompting Methods on ChatGPT's Mathematical Capabilities—0
GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoning—0
From Good to Great: Improving Math Reasoning with Tool-Augmented Interleaf Prompting—0
TinyGSM: achieving >80% on GSM8k with small language models—0
Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning—0
Assessing GPT4-V on Structured Reasoning Tasks—0
Frugal LMs Trained to Invoke Symbolic Solvers Achieve Parameter-Efficient Arithmetic ReasoningCode0
Universal Self-Consistency for Large Language Model Generation—0
LANS: A Layout-Aware Neural Solver for Plane Geometry Problem—0
AlignedCoT: Prompting Large Language Models via Native-Speaking DemonstrationsCode0
Orca 2: Teaching Small Language Models How to Reason—0
First-Step Advantage: Importance of Starting Right in Multi-Step Math Reasoning—0
VerityMath: Advancing Mathematical Reasoning by Self-Verification Through Unit ConsistencyCode0
Let's Reinforce Step by Step—0
ATHENA: Mathematical Reasoning with Thought ExpansionCode0
math-PVS: A Large Language Model Framework to Map Scientific Publications to PVS Theories—0
MCC-KD: Multi-CoT Consistent Knowledge DistillationCode0
MAF: Multi-Aspect Feedback for Improving Reasoning in Large Language ModelsCode0
Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations—0
TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language ModelsCode0
Let's reward step by step: Step-Level reward model as the Navigators for Reasoning—0
DavIR: Data Selection via Implicit Reward for Large Language Models—0
KwaiYiiMath: Technical Report—0
LLM4DV: Using Large Language Models for Hardware Test Stimuli Generation—0
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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