most citedAstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

TVWorld: Foundations for Remote-Control TV Agents

Zhantao Ma, Quanfeng Lu, Shuai Zhong +3

Recent large vision-language models (LVLMs) have demonstrated strong potential for device control. However, existing research has primarily focused on point-and-click (PnC) interac…

astro-ph.IM20251 cited

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

Jinghang Shi, Xiaoyu Tang, Yang Huang +4

Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…

cs.AI2025

SWIRL: A Staged Workflow for Interleaved Reinforcement Learning in Mobile GUI Control

Quanfeng Lu, Zhantao Ma, Shuai Zhong +4

The rapid advancement of large vision language models (LVLMs) and agent systems has heightened interest in mobile GUI agents that can reliably translate natural language into inter…

cs.CV2025

UniFork: Exploring Modality Alignment for Unified Multimodal Understanding and Generation

Teng Li, Quanfeng Lu, Lirui Zhao +5

Unified image understanding and generation has emerged as a promising paradigm in multimodal artificial intelligence. Despite recent progress, the optimal architectural design for…

cs.CV2025

MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning

Fanqing Meng, Lingxiao Du, Zongkai Liu +12

DeepSeek R1, and o1 have demonstrated powerful reasoning capabilities in the text domain through stable large-scale reinforcement learning. To enable broader applications, some wor…

cs.IR20251 cited

LLM4Ranking: An Easy-to-use Framework of Utilizing Large Language Models for Document Reranking

Qi Liu, Haozhe Duan, Yiqun Chen +3

Utilizing large language models (LLMs) for document reranking has been a popular and promising research direction in recent years, many studies are dedicated to improving the perfo…