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Arithmetic Reasoning

Papers

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Showing 101–150 of 175 papers

TitleStatusHype
KwaiYiiMath: Technical Report—0
Mistral 7BCode6
MuggleMath: Assessing the Impact of Query and Response Augmentation on Math ReasoningCode2
DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language ModelsCode1
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical ReasoningCode2
DOMINO: A Dual-System for Multi-step Visual Language ReasoningCode1
A Dynamic LLM-Powered Agent Network for Task-Oriented Agent CollaborationCode1
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem SolvingCode3
Are Human-generated Demonstrations Necessary for In-context Learning?Code1
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language ModelsCode2
OpenChat: Advancing Open-source Language Models with Mixed-Quality DataCode0
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RLCode1
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructCode5
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-VerificationCode2
Token-Scaled Logit Distillation for Ternary Weight Generative Language ModelsCode1
Scaling Relationship on Learning Mathematical Reasoning with Large Language ModelsCode2
Llama 2: Open Foundation and Fine-Tuned Chat ModelsCode8
Model Card and Evaluations for Claude Models—0
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes—0
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMsCode1
DiversiGATE: A Comprehensive Framework for Reliable Large Language Models—0
Boosting Language Models Reasoning with Chain-of-Knowledge PromptingCode1
Prompt Space Optimizing Few-shot Reasoning Success with Large Language ModelsCode0
Encouraging Divergent Thinking in Large Language Models through Multi-Agent DebateCode2
Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models—0
Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic SystemsCode0
A Mechanistic Interpretation of Arithmetic Reasoning in Language Models using Causal Mediation AnalysisCode1
PaD: Program-aided Distillation Can Teach Small Models Reasoning Better than Chain-of-thought Fine-tuningCode0
Automatic Model Selection with Large Language Models for ReasoningCode1
RCOT: Detecting and Rectifying Factual Inconsistency in Reasoning by Reversing Chain-of-Thought—0
Hint of Thought prompting: an explainable and zero-shot approach to reasoning tasks with LLMs—0
Tree of Thoughts: Deliberate Problem Solving with Large Language ModelsCode5
SatLM: Satisfiability-Aided Language Models Using Declarative PromptingCode1
Learning Non-linguistic Skills without Sacrificing Linguistic ProficiencyCode0
CodeT5+: Open Code Large Language Models for Code Understanding and GenerationCode0
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
Self-Evaluation Guided Beam Search for Reasoning—0
Progressive-Hint Prompting Improves Reasoning in Large Language ModelsCode2
When do you need Chain-of-Thought Prompting for ChatGPT?—0
LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language ModelsCode3
Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural NetworksCode1
Sparks of Artificial General Intelligence: Early experiments with GPT-4Code6
GPT-4 Technical ReportCode6
MathPrompter: Mathematical Reasoning using Large Language ModelsCode1
LLaMA: Open and Efficient Foundation Language ModelsCode7
Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataCode1
LEVER: Learning to Verify Language-to-Code Generation with ExecutionCode1
Do Deep Neural Networks Capture Compositionality in Arithmetic Reasoning?Code0
Is ChatGPT a General-Purpose Natural Language Processing Task Solver?Code2
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All datasetsGSM8KMultiArithGame of 24MathMCMathToF

Benchmark Results

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