activity
20222026
most citedLasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model

69 citations · 174 across the 31 of their papers we have counts for

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7 papers · 1 filter

cs.CL2026

ReCite: Agentic Reasoning for Faithful Citation

Yuyang Huang, Bobo Li, Jiajia Song +4

Accurate citations are the foundation of academic writing, tracing intellectual origins and substantiating core claims. However, manually navigating the growing volume of scientifi…

cs.AI2026

OmniScientist: An Omni-Modal Omni-Discipline AI Scientist

Bobo Li, Hao Fei, Tianjie Ju +2

Recent advances in foundation models have enabled AI scientists to automate increasingly complete research workflows, from hypothesis generation and code execution to manuscript pr…

cs.CL2026

MoCA: Implicit Social Context Analysis

Wenhao Xu, Kaiwen Zhang, Hao Li +10

Human social communication, such as affection and intent, is often conveyed in highly implicit ways, where underlying meanings are expressed through indirect, socially and cultural…

cs.AI2026

From Profiling to Synthesis: Benchmarking Implicit Behavioral Alignment in Personalized LLM Agents

Jiajia Song, Bobo Li, Haiwen Yi +6

Large Language Models have enabled increasingly capable autonomous agents, yet personalization remains critical for making such agents practically useful. Recent benchmarks have be…

cs.CV2026

Audio-Visual Intelligence in Large Foundation Models

You Qin, Kai Liu, Shengqiong Wu +12

Audio-Visual Intelligence (AVI) has emerged as a central frontier in artificial intelligence, bridging auditory and visual modalities to enable machines that can perceive, generate…

cs.CL2026

LASQ: A Low-resource Aspect-based Sentiment Quadruple Extraction Dataset

Aizihaierjiang Yusufu, Jiang Liu, Kamran Aziz +5

In recent years, aspect-based sentiment analysis (ABSA) has made rapid progress and shown strong practical value. However, existing research and benchmarks are largely concentrated…

cs.CV2026

Unveiling the Cognitive Compass: Theory-of-Mind-Guided Multimodal Emotion Reasoning

Meng Luo, Bobo Li, Shanqing Xu +8

Despite rapid progress in multimodal large language models (MLLMs), their capability for deep emotional understanding remains limited. We argue that genuine affective intelligence…