SOTAVerified

GSM8K

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–300 of 439 papers

TitleStatusHype
Upweighting Easy Samples in Fine-Tuning Mitigates ForgettingCode0
Reasoning-as-Logic-Units: Scaling Test-Time Reasoning in Large Language Models Through Logic Unit Alignment—0
BARE: Leveraging Base Language Models for Few-Shot Synthetic Data Generation—0
ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference—0
Pheromone-based Learning of Optimal Reasoning Paths—0
RotateKV: Accurate and Robust 2-Bit KV Cache Quantization for LLMs via Outlier-Aware Adaptive Rotations—0
Is your LLM trapped in a Mental Set? Investigative study on how mental sets affect the reasoning capabilities of LLMs—0
DNA 1.0 Technical Report—0
ArithmAttack: Evaluating Robustness of LLMs to Noisy Context in Math Problem SolvingCode0
DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy TheoryCode0
Semantic Exploration with Adaptive Gating for Efficient Problem Solving with Language Models—0
InfiFusion: A Unified Framework for Enhanced Cross-Model Reasoning via LLM Fusion—0
Recursive Decomposition of Logical Thoughts: Framework for Superior Reasoning and Knowledge Propagation in Large Language Models—0
DIVE: Diversified Iterative Self-ImprovementCode0
Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs—0
LLM2: Let Large Language Models Harness System 2 ReasoningCode0
Towards Intrinsic Self-Correction Enhancement in Monte Carlo Tree Search Boosted Reasoning via Iterative Preference Learning—0
System-2 Mathematical Reasoning via Enriched Instruction Tuning—0
Ask-Before-Detection: Identifying and Mitigating Conformity Bias in LLM-Powered Error Detector for Math Word Problem Solutions—0
Inference Scaling vs Reasoning: An Empirical Analysis of Compute-Optimal LLM Problem-SolvingCode0
Enhancing Knowledge Distillation for LLMs with Response-Priming PromptingCode0
Falcon: Faster and Parallel Inference of Large Language Models through Enhanced Semi-Autoregressive Drafting and Custom-Designed Decoding Tree—0
A Graph-Based Synthetic Data Pipeline for Scaling High-Quality Reasoning Instructions—0
Learning to Reason via Self-Iterative Process Feedback for Small Language Models—0
SmolTulu: Higher Learning Rate to Batch Size Ratios Can Lead to Better Reasoning in SLMs—0
Evolutionary Pre-Prompt Optimization for Mathematical Reasoning—0
Training-Free Mitigation of Language Reasoning Degradation After Multimodal Instruction Tuning—0
MALT: Improving Reasoning with Multi-Agent LLM Training—0
Mixture of Cache-Conditional Experts for Efficient Mobile Device Inference—0
Unraveling Arithmetic in Large Language Models: The Role of Algebraic Structures—0
Predicting Emergent Capabilities by Finetuning—0
Patience Is The Key to Large Language Model Reasoning—0
Adaptive Decoding via Latent Preference Optimization—0
Dynamic Subset Tuning: Expanding the Operational Range of Parameter-Efficient Training for Large Language Models—0
Quasi-random Multi-Sample Inference for Large Language Models—0
Reasoning Robustness of LLMs to Adversarial Typographical Errors—0
Kwai-STaR: Transform LLMs into State-Transition Reasoners—0
Self-Consistency Preference Optimization—0
Dictionary Insertion Prompting for Multilingual Reasoning on Multilingual Large Language Models—0
Rethinking Data Synthesis: A Teacher Model Training Recipe with Interpretation—0
ReasonAgain: Using Extractable Symbolic Programs to Evaluate Mathematical Reasoning—0
Adaptive Dense Reward: Understanding the Gap Between Action and Reward Space in Alignment—0
Optimizing Chain-of-Thought Reasoning: Tackling Arranging Bottleneck via Plan Augmentation—0
SMART: Self-learning Meta-strategy Agent for Reasoning TasksCode0
On Designing Effective RL Reward at Training Time for LLM Reasoning—0
TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling—0
SBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented GenerationCode0
Not All Votes Count! Programs as Verifiers Improve Self-Consistency of Language Models for Math ReasoningCode0
MIND: Math Informed syNthetic Dialogues for Pretraining LLMs—0
How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning PerspectiveCode0
Show:102550
← PrevPage 6 of 9Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1XolverAccuracy98.1—Unverified
2Orange-mini0-shot MRR98—Unverified