SOTAVerified

Arithmetic Reasoning

Papers

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Showing 101–150 of 175 papers

TitleStatusHype
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
S^2FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity—0
Self-Evaluation Guided Beam Search for Reasoning—0
Hint of Thought prompting: an explainable and zero-shot approach to reasoning tasks with LLMs—0
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training—0
Skin-in-the-Game: Decision Making via Multi-Stakeholder Alignment in LLMs—0
Small Language Models are Equation Reasoners—0
Solving math word problems with process- and outcome-based feedback—0
SymBa: Symbolic Backward Chaining for Structured Natural Language Reasoning—0
The ART of LLM Refinement: Ask, Refine, and Trust—0
The Claude 3 Model Family: Opus, Sonnet, Haiku—0
The Lottery LLM Hypothesis, Rethinking What Abilities Should LLM Compression Preserve?—0
The Unreasonable Effectiveness of Eccentric Automatic Prompts—0
Think Beyond Size: Adaptive Prompting for More Effective Reasoning—0
Think-to-Talk or Talk-to-Think? When LLMs Come Up with an Answer in Multi-Step Arithmetic Reasoning—0
ThoughtProbe: Classifier-Guided Thought Space Exploration Leveraging LLM Intrinsic Reasoning—0
TinyGSM: achieving >80% on GSM8k with small language models—0
Tokenization Constraints in LLMs: A Study of Symbolic and Arithmetic Reasoning Limits—0
Towards Intrinsic Self-Correction Enhancement in Monte Carlo Tree Search Boosted Reasoning via Iterative Preference Learning—0
Transcending Scaling Laws with 0.1% Extra Compute—0
Unlocking Structured Thinking in Language Models with Cognitive Prompting—0
VisualSphinx: Large-Scale Synthetic Vision Logic Puzzles for RL—0
When do you need Chain-of-Thought Prompting for ChatGPT?—0
Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding—0
Why We Build Local Large Language Models: An Observational Analysis from 35 Japanese and Multilingual LLMs—0
0/1 Deep Neural Networks via Block Coordinate Descent—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