activity
20242026
most citedUnveiling the Impact of Multi-Modal Interactions on User Engagement: A Comprehensive Evaluation in AI-driven Conversations

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

RoTA-Bench: Evaluating 3D Spatial Reasoning through Interactive Projection Alignment

Qingchuan Ma, Yuexiao Ma, Xiang Meng +7

Can vision-language models turn 2D observations into 3D understanding that supports precise action? This requires inferring object geometry, anticipating the effects of rotation, a…

cs.AI2026

A2RBench: An Automatic Paradigm for Formally Verifiable Abstract Reasoning Benchmark Generation

Qingchuan Ma, Yuexiao Ma, Yongkang Xie +3

Abstract reasoning ability reflects the intelligence and generalization capacity of LLMs to extract and apply abstract rules. However, accurately measuring this ability remains cha…

cs.AI2026

SocialOmni: Benchmarking Audio-Visual Social Interactivity in Omni Models

Tianyu Xie, Jinfa Huang, Yuexiao Ma +11

Evaluating omni-modal large language models (OLMs) in multi-party dialogue requires more than answer correctness on pre-segmented inputs. We introduce SocialOmni, an offline diagno…

cs.CL2025

Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective

Qingchuan Ma, Yuhang Wu, Xiawu Zheng +1

In this paper, we aim to establish a simple, effective, and theoretically grounded benchmark for rigorously probing abstract reasoning in Large Language Models (LLMs). To achieve t…

cs.CL2024★ 3 cited

Unveiling the Impact of Multi-Modal Interactions on User Engagement: A Comprehensive Evaluation in AI-driven Conversations

Lichao Zhang, Jia Yu, Shuai Zhang +10

Large Language Models (LLMs) have significantly advanced user-bot interactions, enabling more complex and coherent dialogues. However, the prevalent text-only modality might not fu…