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Arithmetic Reasoning

Papers

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Showing 51–100 of 175 papers

TitleStatusHype
UL2: Unifying Language Learning ParadigmsCode1
Evaluating LLMs' Mathematical and Coding Competency through Ontology-guided InterventionsCode1
Solving Math Word Problems via Cooperative Reasoning induced Language ModelsCode1
Gemini: A Family of Highly Capable Multimodal ModelsCode1
Generative Parameter-Efficient Fine-TuningCode1
Bridging the Gap between Different Vocabularies for LLM EnsembleCode1
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RLCode1
HALO: Hierarchical Autonomous Logic-Oriented Orchestration for Multi-Agent LLM SystemsCode1
Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive PrinciplesCode1
A Mechanistic Interpretation of Arithmetic Reasoning in Language Models using Causal Mediation AnalysisCode1
IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language ReasoningCode1
Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought PromptingCode1
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMsCode1
Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic ReasoningCode1
LEVER: Learning to Verify Language-to-Code Generation with ExecutionCode1
Is the Reversal Curse a Binding Problem? Uncovering Limitations of Transformers from a Basic Generalization FailureCode1
Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural NetworksCode1
MoT: Memory-of-Thought Enables ChatGPT to Self-ImproveCode1
Language Imbalance Driven Rewarding for Multilingual Self-improvingCode1
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human AnnotationsCode1
Large Language Models are Better Reasoners with Self-VerificationCode1
MathPrompter: Mathematical Reasoning using Large Language ModelsCode1
Large Language Models Can Be Easily Distracted by Irrelevant ContextCode1
Turning Dust into Gold: Distilling Complex Reasoning Capabilities from LLMs by Leveraging Negative DataCode1
An Investigation of Neuron Activation as a Unified Lens to Explain Chain-of-Thought Eliciting Arithmetic Reasoning of LLMsCode1
SatLM: Satisfiability-Aided Language Models Using Declarative PromptingCode1
Rethinking Addressing in Language Models via Contexualized Equivariant Positional EncodingCode1
OVM, Outcome-supervised Value Models for Planning in Mathematical ReasoningCode1
Are Human-generated Demonstrations Necessary for In-context Learning?Code1
Distillation Contrastive Decoding: Improving LLMs Reasoning with Contrastive Decoding and DistillationCode1
Learning Math Reasoning from Self-Sampled Correct and Partially-Correct SolutionsCode1
Prompt Optimization via Adversarial In-Context LearningCode1
Arithmetic Without Algorithms: Language Models Solve Math With a Bag of HeuristicsCode1
DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language ModelsCode1
QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor AdaptationCode1
Neuro-Symbolic Integration Brings Causal and Reliable Reasoning ProofsCode1
Toward Adaptive Reasoning in Large Language Models with Thought RollbackCode1
Your Language Model May Think Too Rigidly: Achieving Reasoning Consistency with Symmetry-Enhanced Training—0
Leveraging LLM Reasoning Enhances Personalized Recommender Systems—0
Arithmetic Reasoning with LLM: Prolog Generation & Permutation—0
Evaluating LLMs' Mathematical Reasoning in Financial Document Question Answering—0
Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning—0
Can LLMs Maintain Fundamental Abilities under KV Cache Compression?—0
CLoQ: Enhancing Fine-Tuning of Quantized LLMs via Calibrated LoRA Initialization—0
Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models—0
Composing Ensembles of Pre-trained Models via Iterative Consensus—0
DiversiGATE: A Comprehensive Framework for Reliable Large Language Models—0
DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models—0
Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment—0
Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting—0
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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