15 citations · 15 across the 5 of their papers we have counts for
6 papers
PreciseCoder: Faithful and Generalizable Debugging Beyond Unit-Test Rewards
Yunkai Zhan, Miaosen Chai, Shangshang Wang +5
Reinforcement learning (RL) from unit tests is the common recipe for post-training code models, but a unit test only asks whether the final program passes. We analyze what this uni…
Precise Debugging Benchmark: Is Your Model Debugging or Regenerating?
Wang Bill Zhu, Miaosen Chai, Shangshang Wang +5
Unlike code completion, debugging requires localizing faults and applying targeted edits. We observe that frontier LLMs often regenerate correct but over-edited solutions during de…
Generating Complex Code Analyzers from Natural Language Questions
Amirmohammad Nazari, Sadra Sabouri, Wang Bill Zhu +3
Many software development tasks, such as implementing features and fixing bugs, begin with developers posing questions about a codebase. However, answering questions about codebase…
Algorithmic Primitives of Theory of Mind Benchmarks
Wang Bill Zhu, Qiutong Tony Yi, Robin Jia +1
Do Theory of Mind (ToM) benchmarks really test theory of mind, or are they actually testing parsing and algorithmic state tracking? While benchmarks vary modality and dialogue leng…
Self-Evolving LLM Memory Extraction Across Heterogeneous Tasks
Yuqing Yang, Tengxiao Liu, Wang Bill Zhu +3
As LLM-based assistants become persistent and personalized, they must extract and retain useful information from past conversations as memory. However, the types of information wor…
Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation
Zhiting Hu, Haoran Shi, Bowen Tan +12
We introduce Texar, an open-source toolkit aiming to support the broad set of text generation tasks that transform any inputs into natural language, such as machine translation, su…