collaborators

5 papers

cs.CL2026

Learning to Detect UI Principle Violations via Reinforcement Learning

Nishi Mehta, Swathi Alse, Himani Kumavat +3

Small language models and coding agents increasingly generate web front-end code, yet their outputs are typically evaluated primarily for functional correctness. A generated interf…

cs.DB2026

DPC: Training-Free Text-to-SQL Candidate Selection via Dual-Paradigm Consistency

Boyan Li, Ou Ocean Kun Hei, Yue Yu +1

While Large Language Models (LLMs) demonstrate impressive proficiency in generating SQL queries, they fundamentally lack the capability to self-evaluate correctness without an exec…

cs.CL2026

Judge Like Human Examiners: A Weighted Importance Multi-Point Evaluation Framework for Generative Tasks with Long-form Answers

Guoxin Yu, Chulun Zhou, Lemao Liu +7

Evaluating the quality of model responses remains challenging in generative tasks with long-form answers, as the expected answers usually contain multiple semantically distinct yet…

cs.IR2026

C-Cite: Contextual-Aware Citation Generation for Attributed Large Language Models

Yue Yu, Ting Bai, HengZhi Lan +6

The attribution technique enhances the credibility of LLMs by adding citations to the generated sentences, enabling users to trace back to the original sources and verify the relia…

cs.AI2025

LightSearcher: Efficient DeepSearch via Experiential Memory

Hengzhi Lan, Yue Yu, Li Qian +5

DeepSearch paradigms have become a core enabler for deep reasoning models, allowing them to invoke external search tools to access up-to-date, domain-specific knowledge beyond para…