activity
20202026
most citedLAMOST Medium-Resolution Spectroscopic Survey (LAMOST-MRS): Scientific goals and survey plan

45 citations · 48 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

How Well Do Models Follow Visual Instructions? VIBE: A Systematic Benchmark for Visual Instruction-Driven Image Editing

Huanyu Zhang, Xuehai Bai, Chengzu Li +9

Recent generative models have achieved remarkable progress in image editing. However, existing systems and benchmarks remain largely text-guided. In contrast, human communication i…

astro-ph.IM2025★ 1 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.CV2025

BaseReward: A Strong Baseline for Multimodal Reward Model

Yi-Fan Zhang, Haihua Yang, Huanyu Zhang +11

The rapid advancement of Multimodal Large Language Models (MLLMs) has made aligning them with human preferences a critical challenge. Reward Models (RMs) are a core technology for…

cs.AI2025

RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark

Yang Shi, Yuhao Dong, Yue Ding +22

The integration of visual understanding and generation into unified multimodal models represents a significant stride toward general-purpose AI. However, a fundamental question rem…

cs.CL2025★ 1 cited

MM-RLHF: The Next Step Forward in Multimodal LLM Alignment

Yi-Fan Zhang, Tao Yu, Haochen Tian +17

Despite notable advancements in Multimodal Large Language Models (MLLMs), most state-of-the-art models have not undergone thorough alignment with human preferences. This gap exists…

cs.CV2024★ 1 cited

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?

Yi-Fan Zhang, Huanyu Zhang, Haochen Tian +10

Comprehensive evaluation of Multimodal Large Language Models (MLLMs) has recently garnered widespread attention in the research community. However, we observe that existing benchma…

astro-ph.SR2020★ 45 cited

LAMOST Medium-Resolution Spectroscopic Survey (LAMOST-MRS): Scientific goals and survey plan

Chao Liu, Jianning Fu, Jianrong Shi +38

Since September 2018, LAMOST starts a new 5-year medium-resolution spectroscopic survey (MRS) using bright/gray nights. We present the scientific goals of LAMOST-MRS and propose a…