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Showing 301–325 of 1596 papers

TitleStatusHype
Think Twice: Enhancing LLM Reasoning by Scaling Multi-round Test-time Thinking—0
Scaling Evaluation-time Compute with Reasoning Models as Process Evaluators—0
1.4 Million Open-Source Distilled Reasoning Dataset to Empower Large Language Model Training—0
LogQuant: Log-Distributed 2-Bit Quantization of KV Cache with Superior Accuracy PreservationCode1
Overcoming Vocabulary Mismatch: Vocabulary-agnostic Teacher Guided Language Modeling—0
Activation Functions Considered Harmful: Recovering Neural Network Weights through Controlled Channels—0
SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the WildCode7
Reasoning to Learn from Latent ThoughtsCode2
Teaching LLMs for Step-Level Automatic Math Correction via Reinforcement Learning—0
Long Is More Important Than Difficult for Training Reasoning Models—0
MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection—0
AgentRxiv: Towards Collaborative Autonomous ResearchCode9
Lost in Cultural Translation: Do LLMs Struggle with Math Across Cultural Contexts?Code0
ChatBench: From Static Benchmarks to Human-AI EvaluationCode0
FastCuRL: Curriculum Reinforcement Learning with Progressive Context Extension for Efficient Training R1-like Reasoning ModelsCode2
Exploring the Hidden Reasoning Process of Large Language Models by Misleading Them—0
Tapered Off-Policy REINFORCE: Stable and efficient reinforcement learning for LLMs—0
BurTorch: Revisiting Training from First Principles by Coupling Autodiff, Math Optimization, and Systems—0
Improving Complex Reasoning with Dynamic Prompt Corruption: A soft prompt Optimization Approach—0
xLSTM 7B: A Recurrent LLM for Fast and Efficient InferenceCode7
Pensez: Less Data, Better Reasoning -- Rethinking French LLM—0
EXAONE Deep: Reasoning Enhanced Language ModelsCode1
SPIN-Bench: How Well Do LLMs Plan Strategically and Reason Socially?—0
Chat-TS: Enhancing Multi-Modal Reasoning Over Time-Series and Natural Language Data—0
Understanding the Logical Capabilities of Large Language Models via Out-of-Context Representation Learning—0
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