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Papers

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Showing 226–250 of 439 papers

TitleStatusHype
SOLAR: Scalable Optimization of Large-scale Architecture for Reasoning—0
DeLTa: A Decoding Strategy based on Logit Trajectory Prediction Improves Factuality and Reasoning AbilityCode0
Self-Evolved Preference Optimization for Enhancing Mathematical Reasoning in Small Language Models—0
CODI: Compressing Chain-of-Thought into Continuous Space via Self-DistillationCode0
Layer-Aware Task Arithmetic: Disentangling Task-Specific and Instruction-Following Knowledge—0
Weaker LLMs' Opinions Also Matter: Mixture of Opinions Enhances LLM's Mathematical Reasoning—0
Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones?—0
SECURA: Sigmoid-Enhanced CUR Decomposition with Uninterrupted Retention and Low-Rank Adaptation in Large Language Models—0
LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-Disjoint—0
Dynamic Parallel Tree Search for Efficient LLM Reasoning—0
Earlier Tokens Contribute More: Learning Direct Preference Optimization From Temporal Decay PerspectiveCode0
NLoRA: Nyström-Initiated Low-Rank Adaptation for Large Language ModelsCode0
From Correctness to Comprehension: AI Agents for Personalized Error Diagnosis in Education—0
TreeCut: A Synthetic Unanswerable Math Word Problem Dataset for LLM Hallucination EvaluationCode0
Integrating Arithmetic Learning Improves Mathematical Reasoning in Smaller Models—0
MathFimer: Enhancing Mathematical Reasoning by Expanding Reasoning Steps through Fill-in-the-Middle Task—0
Leveraging Uncertainty Estimation for Efficient LLM Routing—0
Balancing the Budget: Understanding Trade-offs Between Supervised and Preference-Based Finetuning—0
Uncertainty-Aware Search and Value Models: Mitigating Search Scaling Flaws in LLMs—0
Don't Get Lost in the Trees: Streamlining LLM Reasoning by Overcoming Tree Search Exploration PitfallsCode0
Hybrid Offline-online Scheduling Method for Large Language Model Inference Optimization—0
Cost-Saving LLM Cascades with Early Abstention—0
Mathematical Reasoning in Large Language Models: Assessing Logical and Arithmetic Errors across Wide Numerical RangesCode0
Self-Training Large Language Models for Tool-Use Without Demonstrations—0
Evolving LLMs' Self-Refinement Capability via Iterative Preference Optimization—0
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Benchmark Results

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