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20202026
most citedDo Multi-Hop Question Answering Systems Know How to Answer the Single-Hop Sub-Questions?

2 citations · 4 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024★ 2 cited

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…

cs.CL2020★ 2 cited

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…