SWE-Perf: Can Language Models Optimize Code Performance on Real-World Repositories? Paper • 2507.12415 • Published 21 days ago • 41
ZeCO: Zero Communication Overhead Sequence Parallelism for Linear Attention Paper • 2507.01004 • Published Jul 1 • 10
VisCoder: Fine-Tuning LLMs for Executable Python Visualization Code Generation Paper • 2506.03930 • Published Jun 4 • 25
Unleashing the Reasoning Potential of Pre-trained LLMs by Critique Fine-Tuning on One Problem Paper • 2506.03295 • Published Jun 3 • 17
StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs Paper • 2505.20139 • Published May 26 • 18
StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs Paper • 2505.20139 • Published May 26 • 18
QuickVideo: Real-Time Long Video Understanding with System Algorithm Co-Design Paper • 2505.16175 • Published May 22 • 42
General-Reasoner: Advancing LLM Reasoning Across All Domains Paper • 2505.14652 • Published May 20 • 23
Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning Paper • 2503.06034 • Published Mar 8 • 1
Tevatron 2.0: Unified Document Retrieval Toolkit across Scale, Language, and Modality Paper • 2505.02466 • Published May 5 • 1
General-Reasoner: Advancing LLM Reasoning Across All Domains Paper • 2505.14652 • Published May 20 • 23
General-Reasoner: Advancing LLM Reasoning Across All Domains Paper • 2505.14652 • Published May 20 • 23
ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations Paper • 2504.00824 • Published Apr 1 • 44
ScholarCopilot: Training Large Language Models for Academic Writing with Accurate Citations Paper • 2504.00824 • Published Apr 1 • 44
Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows Paper • 2411.07763 • Published Nov 12, 2024 • 2