activity
20242026
most citedSuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

OProver: A Unified Framework for Agentic Formal Theorem Proving

David Ma, Kaijing Ma, Shawn Guo +7

Recent progress in formal theorem proving has benefited from large-scale proof generation and verifier-aware training, but agentic proving is rarely integrated into prover training…

cs.CV2025

ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding

David Ma, Huaqing Yuan, Xingjian Wang +16

Although long-video understanding demands that models capture hierarchical temporal information -- from clip (seconds) and shot (tens of seconds) to event (minutes) and story (hour…

cs.CV2025

IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMs

David Ma, Yuanxing Zhang, Jincheng Ren +17

Existing evaluation frameworks for Multimodal Large Language Models (MLLMs) primarily focus on image reasoning or general video understanding tasks, largely overlooking the signifi…

cs.CL2025★ 4 cited

SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

P Team, Xinrun Du, Yifan Yao +94

Large language models (LLMs) have demonstrated remarkable proficiency in mainstream academic disciplines such as mathematics, physics, and computer science. However, human knowledg…

cs.AI2024★ 1 cited

AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions

Ziming Li, Qianbo Zang, David Ma +11

Data science tasks involving tabular data present complex challenges that require sophisticated problem-solving approaches. We propose AutoKaggle, a powerful and user-centric frame…