2 citations · 4 across the 8 of their papers we have counts for
8 papers
SPARROW: Scalable Taxonomy Induction via Structure-Preserving Partitioning and Constraint-Guided Merging
Yirui Zhang, Yixuan Tang, Yandong Sun +2
Taxonomy induction aims to organize concept sets into coherent hierarchical structures. Recent LLM-based methods can induce taxonomies directly from flat term lists, avoiding the n…
CDEG: Learning Decision-Critical Evidence for Long-Horizon Diagnostic Agents
Xiwei Dai, Zijie Meng, Zhiting Fan +4
Unlike static medical question answering, long-horizon diagnosis captures the sequential nature of clinical practice: evidence is progressively acquired, integrated, and evaluated…
DentAgent: Evidence-Centric Multi-Agent Coordination for Multimodal Dental Reasoning
Zijie Meng, Xiwei Dai, Yixuan Tang +6
Oral diseases affect billions of people worldwide, underscoring a pressing need for accurate and reliable dental assessment that integrates heterogeneous evidence from domain knowl…
A-TMA: Decoupling State-Aware Memory Failures in Long-Term Agent Memory
Zitong Shi, Yixuan Tang, Anthony Kum Hoe Tung
Long term memory lets LLM agents act as persistent assistants, but user facts change. A useful memory system must know what is true now, what used to be true, and what changed. We…
MPCG: Multi-Round Persona-Conditioned Generation for Modeling the Evolution of Misinformation with LLMs
Jun Rong Brian Chong, Yixuan Tang, Anthony K. H. Tung
Misinformation evolves as it spreads, shifting in language, framing, and moral emphasis to adapt to new audiences. However, current misinformation detection approaches implicitly a…
The Missing Parts: Augmenting Fact Verification with Half-Truth Detection
Yixuan Tang, Jincheng Wang, Anthony K. H. Tung
Fact verification systems typically assess whether a claim is supported by retrieved evidence, assuming that truthfulness depends solely on what is stated. However, many real-world…
A General Framework for Producing Interpretable Semantic Text Embeddings
Yiqun Sun, Qiang Huang, Yixuan Tang +2
Semantic text embedding is essential to many tasks in Natural Language Processing (NLP). While black-box models are capable of generating high-quality embeddings, their lack of int…
Do Multi-Hop Question Answering Systems Know How to Answer the Single-Hop Sub-Questions?
Yixuan Tang, Hwee Tou Ng, Anthony K. H. Tung
Multi-hop question answering (QA) requires a model to retrieve and integrate information from different parts of a long text to answer a question. Humans answer this kind of comple…