activity
20242026
collaborators

13 papers

cs.SE2026

SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?

Jeffrey Jian Ma, Milad Hashemi, Amir Yazdanbakhsh +5

Optimizing the performance of large-scale software repositories demands expertise in code reasoning and software engineering (SWE) to reduce runtime while preserving program correc…

cs.AI2026

VideoGameBench: Can Vision-Language Models complete popular video games?

Alex L. Zhang, Thomas L. Griffiths, Karthik R. Narasimhan +1

Vision-language models (VLMs) have achieved strong results on coding and math benchmarks that are challenging for humans, yet their ability to perform tasks that come naturally to…

cs.SE2026

CodeClash: Benchmarking Goal-Oriented Software Engineering

John Yang, Kilian Lieret, Joyce Yang +6

Current benchmarks for coding evaluate language models (LMs) on concrete, well-specified tasks such as fixing specific bugs or writing targeted tests. However, human programmers do…

cs.AI2026

Probing the Critical Point (CritPt) of AI Reasoning: a Frontier Physics Research Benchmark

Minhui Zhu, Minyang Tian, Xiaocheng Yang +61

While large language models (LLMs) with reasoning capabilities are progressing rapidly on high-school math competitions and coding, can they reason effectively through complex, ope…

cs.SE2026

ProgramBench: Can Language Models Rebuild Programs From Scratch?

John Yang, Kilian Lieret, Jeffrey Ma +9

Turning ideas into full software projects from scratch has become a popular use case for language models. Agents are being deployed to seed, maintain, and grow codebases over exten…

cs.SE2025

AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs?

Ori Press, Brandon Amos, Haoyu Zhao +21

Despite progress in language model (LM) capabilities, evaluations have thus far focused on models' performance on tasks that humans have previously solved, including in programming…