activity
20232026
most citedML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code

2 citations · 3 across the 16 of their papers we have counts for

collaborators
Showing 2026Show all

6 papers · 1 filter

cs.CV2026

Towards Characterizing Scientific Image Utility and Upgradability

WenZhe Li, Qihang Yan, Liang Chen +6

Scientific images function as critical evidence in research communication, yet their integrity faces unprecedented threats from AI-generated content that introduces subtle but cons…

cs.CV2026

Crafter: A Multi-Agent Harness for Editable Scientific Figure Generation from Diverse Inputs

Haozhe Zhao, Shuzheng Si, Zhenhailong Wang +6

Scientific figures are among the most effective means of communicating complex research ideas, yet producing publication-quality illustrations remains one of the most labor-intensi…

cs.AI2026

SaaS-Bench: Can Computer-Use Agents Leverage Real-World SaaS to Solve Professional Workflows?

Kean Shi, Zihang Li, Tianyi Ma +13

Computer-Using Agents (CUAs) are rapidly extending large language models (LLMs) beyond text-based reasoning toward action execution in more complex environments, such as web browse…

cs.SE2026

RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades

Xinbo Xu, Ruihan Yang, Haiyang Shen +13

Coding agents are increasingly deployed in real software development, where a single version iteration requires months of coordinated work across many files. However, most existing…

cs.LG2026

Step-wise Rubric Rewards for LLM Reasoning

Weichu Xie, Haozhe Zhao, Wenpu Liu +15

Reinforcement Learning with Verifiable Rewards (RLVR) is widely used to improve reasoning in large language models, but rewards only final-answer correctness with no supervision ov…

cs.CL2026

VCG-Bench: Towards A Unified Visual-Centric Benchmark for Structured Generation and Editing

Xiaoyan Su, Peijie Dong, Zhenheng Tang +8

Despite the rapid advancements in Vision-Language Models (VLMs), a critical gap remains in their ability to handle structured, controllable diagrammatic tasks essential for profess…