SOTAVerified

Arithmetic Reasoning

Papers

Showing 51100 of 175 papers

TitleStatusHype
Evaluating LLMs' Mathematical and Coding Competency through Ontology-guided InterventionsCode1
Turning Dust into Gold: Distilling Complex Reasoning Capabilities from LLMs by Leveraging Negative DataCode1
Gemini: A Family of Highly Capable Multimodal ModelsCode1
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human AnnotationsCode1
Prompt Optimization via Adversarial In-Context LearningCode1
Generative Parameter-Efficient Fine-TuningCode1
Neuro-Symbolic Integration Brings Causal and Reliable Reasoning ProofsCode1
OVM, Outcome-supervised Value Models for Planning in Mathematical ReasoningCode1
Empirical Study of Zero-Shot NER with ChatGPTCode1
DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language ModelsCode1
DOMINO: A Dual-System for Multi-step Visual Language ReasoningCode1
A Dynamic LLM-Powered Agent Network for Task-Oriented Agent CollaborationCode1
Are Human-generated Demonstrations Necessary for In-context Learning?Code1
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RLCode1
Token-Scaled Logit Distillation for Ternary Weight Generative Language ModelsCode1
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMsCode1
Boosting Language Models Reasoning with Chain-of-Knowledge PromptingCode1
A Mechanistic Interpretation of Arithmetic Reasoning in Language Models using Causal Mediation AnalysisCode1
Automatic Model Selection with Large Language Models for ReasoningCode1
SatLM: Satisfiability-Aided Language Models Using Declarative PromptingCode1
Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought PromptingCode1
MoT: Memory-of-Thought Enables ChatGPT to Self-ImproveCode1
Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural NetworksCode1
MathPrompter: Mathematical Reasoning using Large Language ModelsCode1
Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataCode1
LEVER: Learning to Verify Language-to-Code Generation with ExecutionCode1
Large Language Models Can Be Easily Distracted by Irrelevant ContextCode1
Batch Prompting: Efficient Inference with Large Language Model APIsCode1
Large Language Models are Better Reasoners with Self-VerificationCode1
Solving Math Word Problems via Cooperative Reasoning induced Language ModelsCode1
OpenCQA: Open-ended Question Answering with ChartsCode1
Learning Math Reasoning from Self-Sampled Correct and Partially-Correct SolutionsCode1
UL2: Unifying Language Learning ParadigmsCode1
Self-Consistency Improves Chain of Thought Reasoning in Language ModelsCode1
IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language ReasoningCode1
Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic ReasoningCode1
Learning to Reason for Text Generation from Scientific TablesCode1
DCR: Quantifying Data Contamination in LLMs EvaluationCode0
DS@GT at CheckThat! 2025: Evaluating Context and Tokenization Strategies for Numerical Fact VerificationCode0
FinLMM-R1: Enhancing Financial Reasoning in LMM through Scalable Data and Reward Design0
Mathematical Reasoning for Unmanned Aerial Vehicles: A RAG-Based Approach for Complex Arithmetic ReasoningCode0
Learning-at-Criticality in Large Language Models for Quantum Field Theory and Beyond0
DiaBlo: Diagonal Blocks Are Sufficient For FinetuningCode0
VisualSphinx: Large-Scale Synthetic Vision Logic Puzzles for RL0
Joint Flashback Adaptation for Forgetting-Resistant Instruction Tuning0
Tokenization Constraints in LLMs: A Study of Symbolic and Arithmetic Reasoning Limits0
OMAC: A Broad Optimization Framework for LLM-Based Multi-Agent CollaborationCode0
Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.50
ThoughtProbe: Classifier-Guided Thought Space Exploration Leveraging LLM Intrinsic Reasoning0
Your Language Model May Think Too Rigidly: Achieving Reasoning Consistency with Symmetry-Enhanced Training0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Claude 3.5 Sonnet (HPT)Accuracy97.72Unverified
2DUP prompt upon GPT-4Accuracy97.1Unverified
3Qwen2-Math-72B-Instruct (greedy)Accuracy96.7Unverified
4SFT-Mistral-7B (Metamath, OVM, Smart Ensemble)Accuracy96.4Unverified
5OpenMath2-Llama3.1-70B (majority@256)Accuracy96Unverified
6Jiutian-大模型Accuracy95.2Unverified
7DAMOMath-7B(MetaMath, OVM, BS, Ensemble)Accuracy95.1Unverified
8Claude 3 Opus (0-shot chain-of-thought)Accuracy95Unverified
9OpenMath2-Llama3.1-70BAccuracy94.9Unverified
10GPT-4 (Teaching-Inspired)Accuracy94.8Unverified
#ModelMetricClaimedVerifiedStatus
1Text-davinci-002 (175B)(zero-shot-cot)Accuracy78.7Unverified
2Text-davinci-002 (175B) (zero-shot)Accuracy17.7Unverified
#ModelMetricClaimedVerifiedStatus
1Tree of Thoughts (b=5)Success0.74Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4 (Teaching-Inspired)Accuracy92.2Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4 (Teaching-Inspired)Accuracy89.2Unverified