6 papers
Evo-Bench: Can Language Models Improve Agent Harness?
Lisheng Huang, Chen Yang, Hao Zhou +6
Large Language Models (LLMs) have driven rapid progress in autonomous agents, yet standard evaluations remain confined to static task solving. An emerging frontier is harness evolu…
Training Transformers as a Universal Computer
Ruize Xu, Chenxiao Yang, Yanhong Li +1
We demonstrate that a small transformer can learn to execute programs in MicroPy, a simplified yet computationally universal programming language. Given procedure definitions toget…
Uncovering Business Logic Bugs via Semantics-Driven Unit Test Generation
Chen Yang, Junjie Chen
Business logic bugs violate intended business semantics and are particularly prevalent in enterprise software. Yet most existing unit test generation techniques are code-centric, m…
PACE: Prefix-Protected and Difficulty-Aware Compression for Efficient Reasoning
Ruixiang Feng, Yuntao Wen, Silin Zhou +14
Language Reasoning Models (LRMs) achieve strong performance by scaling test-time computation but often suffer from ``overthinking'', producing excessively long reasoning traces tha…
Nanbeige4-3B Technical Report: Exploring the Frontier of Small Language Models
Chen Yang, Guangyue Peng, Jiaying Zhu +16
We present Nanbeige4-3B, a family of small-scale but high-performing language models. Pretrained on 23T high-quality tokens and finetuned on over 30 million diverse instructions, w…
CoSineVerifier: Tool-Augmented Answer Verification for Computation-Oriented Scientific Questions
Ruixiang Feng, Zhenwei An, Yuntao Wen +9
Answer verification methods are widely employed in language model training pipelines spanning data curation, evaluation, and reinforcement learning with verifiable rewards (RLVR).…