6 citations · 8 across the 4 of their papers we have counts for
6 papers
Confidence Geometry Reveals Trace-Level Correctness in Large Language Model Reasoning
Shuo Liu, Ding Liu, Shi-Ju Ran
Large language models (LLMs) generate not only reasoning text, but also token-level confidence trajectories that record how uncertainty evolves during inference. Whether these traj…
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…
OpenING: A Comprehensive Benchmark for Judging Open-ended Interleaved Image-Text Generation
Pengfei Zhou, Xiaopeng Peng, Jiajun Song +15
Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding and generation tasks. However, generating interleaved image-text content remains a ch…
SearchLVLMs: A Plug-and-Play Framework for Augmenting Large Vision-Language Models by Searching Up-to-Date Internet Knowledge
Chuanhao Li, Zhen Li, Chenchen Jing +6
Large vision-language models (LVLMs) are ignorant of the up-to-date knowledge, such as LLaVA series, because they cannot be updated frequently due to the large amount of resources…
ConvBench: A Multi-Turn Conversation Evaluation Benchmark with Hierarchical Capability for Large Vision-Language Models
Shuo Liu, Kaining Ying, Hao Zhang +8
This paper presents ConvBench, a novel multi-turn conversation evaluation benchmark tailored for Large Vision-Language Models (LVLMs). Unlike existing benchmarks that assess indivi…
MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
Kaining Ying, Fanqing Meng, Jin Wang +19
Large Vision-Language Models (LVLMs) show significant strides in general-purpose multimodal applications such as visual dialogue and embodied navigation. However, existing multimod…