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Arithmetic Reasoning

Papers

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Showing 101–150 of 175 papers

TitleStatusHype
Overcoming Barriers to Skill Injection in Language Modeling: Case Study in ArithmeticCode0
OMAC: A Broad Optimization Framework for LLM-Based Multi-Agent CollaborationCode0
Learning Non-linguistic Skills without Sacrificing Linguistic ProficiencyCode0
DCR: Quantifying Data Contamination in LLMs EvaluationCode0
Least-to-Most Prompting Enables Complex Reasoning in Large Language ModelsCode0
3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and ComposabilityCode0
Improving Arithmetic Reasoning Ability of Large Language Models through Relation Tuples, Verification and Dynamic FeedbackCode0
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language ModelsCode0
Frugal LMs Trained to Invoke Symbolic Solvers Achieve Parameter-Efficient Arithmetic ReasoningCode0
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLMCode0
LLM Augmented LLMs: Expanding Capabilities through CompositionCode0
Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language ModelsCode0
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
Exploring Group and Symmetry Principles in Large Language Models—0
Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.5—0
Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together—0
FinLMM-R1: Enhancing Financial Reasoning in LMM through Scalable Data and Reward Design—0
GaLore+: Boosting Low-Rank Adaptation for LLMs with Cross-Head Projection—0
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes—0
Hint Marginalization for Improved Reasoning in Large Language Models—0
Inference-Time Computations for LLM Reasoning and Planning: A Benchmark and Insights—0
Joint Flashback Adaptation for Forgetting-Resistant Instruction Tuning—0
KwaiYiiMath: Technical Report—0
Large Language Models are Null-Shot Learners—0
Large Language Models Can Self-Correct with Key Condition Verification—0
Large Language Models Can Self-Improve—0
Learning-at-Criticality in Large Language Models for Quantum Field Theory and Beyond—0
Model Card and Evaluations for Claude Models—0
Neural-Symbolic Recursive Machine for Systematic Generalization—0
NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks—0
On Representational Dissociation of Language and Arithmetic in Large Language Models—0
Making Large Language Models Better Reasoners with Step-Aware Verifier—0
Orca 2: Teaching Small Language Models How to Reason—0
Orca-Math: Unlocking the potential of SLMs in Grade School Math—0
PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model—0
Prompt Sketching for Large Language Models—0
RCOT: Detecting and Rectifying Factual Inconsistency in Reasoning by Reversing Chain-of-Thought—0
Relating the Seemingly Unrelated: Principled Understanding of Generalization for Generative Models in Arithmetic Reasoning Tasks—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