activity
20172026
most citedDeep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies

160 citations · 246 across the 35 of their papers we have counts for

collaborators

42 papers

cs.CL2026

Taming Actor-Observer Asymmetry in Agents via Dialectical Alignment

Bobo Li, Rui Wu, Zibo Ji +5

Large Language Model agents have rapidly evolved from static text generators into dynamic systems capable of executing complex autonomous workflows. To enhance reliability, multi-a…

cs.CL2026

Asking the Right Questions: Ontology-Grounded Interpretable Embeddings for Biomedical Text

Yixuan Tang, Zhenghong Lin, Yandong Sun +3

While dense biomedical embeddings achieve strong performance, their opaque dimensions limit transparency in biomedical NLP. Recent question-based interpretable embeddings represent…

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…

cs.HC2026

Althea: The Fact-Checking--Metalearning Tradeoff in AI-Assisted Verification

Svetlana Churina, Kokil Jaidka, Anab Maulana Barik +5

Fact-checking systems must be scalable and epistemically trustworthy. We introduce Althea, a retrieval-augmented system for user-driven claim evaluation that matches standard pipel…

cs.CL2026

LogicReward: Incentivizing LLM Reasoning via Step-Wise Logical Supervision

Jundong Xu, Hao Fei, Huichi Zhou +6

Although LLMs exhibit strong reasoning capabilities, existing training methods largely depend on outcome-based feedback, which can produce correct answers with flawed reasoning. Pr…

cs.CV2025

Multi-Part Object Representations via Graph Structures and Co-Part Discovery

Alex Foo, Wynne Hsu, Mong Li Lee

Discovering object-centric representations from images can significantly enhance the robustness, sample efficiency and generalizability of vision models. Works on images with multi…