11 citations · 27 across the 50 of their papers we have counts for
8 papers · 1 filter
Multimodal Hypothetical Summary for Retrieval-based Multi-image Question Answering
Peize Li, Qingyi Si, Peng Fu +2
Retrieval-based multi-image question answering (QA) task involves retrieving multiple question-related images and synthesizing these images to generate an answer. Conventional "ret…
ReTaKe: Reducing Temporal and Knowledge Redundancy for Long Video Understanding
Xiao Wang, Qingyi Si, Jianlong Wu +3
Video Large Language Models (VideoLLMs) have made significant strides in video understanding but struggle with long videos due to the limitations of their backbone LLMs. Existing s…
A Multi-Task Role-Playing Agent Capable of Imitating Character Linguistic Styles
Siyuan Chen, Qingyi Si, Chenxu Yang +4
The advent of large language models (LLMs) has significantly propelled the advancement of Role-Playing Agents (RPAs). However, current Role-Playing Agents predominantly focus on mi…
Towards Flexible Evaluation for Generative Visual Question Answering
Huishan Ji, Qingyi Si, Zheng Lin +1
Throughout rapid development of multimodal large language models, a crucial ingredient is a fair and accurate evaluation of their multimodal comprehension abilities. Although Visua…
Multimodal Table Understanding
Mingyu Zheng, Xinwei Feng, Qingyi Si +4
Although great progress has been made by previous table understanding methods including recent approaches based on large language models (LLMs), they rely heavily on the premise th…
Think out Loud: Emotion Deducing Explanation in Dialogues
Jiangnan Li, Zheng Lin, Lanrui Wang +6
Humans convey emotions through daily dialogues, making emotion understanding a crucial step of affective intelligence. To understand emotions in dialogues, machines are asked to re…
Towards Unified Interactive Visual Grounding in The Wild
Jie Xu, Hanbo Zhang, Qingyi Si +3
Interactive visual grounding in Human-Robot Interaction (HRI) is challenging yet practical due to the inevitable ambiguity in natural languages. It requires robots to disambiguate…
Are Large Language Models Table-based Fact-Checkers?
Hanwen Zhang, Qingyi Si, Peng Fu +2
Table-based Fact Verification (TFV) aims to extract the entailment relation between statements and structured tables. Existing TFV methods based on small-scaled models suffer from…