collaborators

6 papers

cs.CL2026

CAReDiO: Cultural Alignment via Representativeness and Distinctiveness Guided Data Optimization

Jing Yao, Xiaoyuan Yi, Jindong Wang +2

As Large Language Models (LLMs) are deployed across diverse regions, aligning them with pluralistic cultures is crucial for improving user engagement and mitigating cultural confli…

cs.CL2026

Harnessing Temporal Databases for Systematic Evaluation of Factual Time-Sensitive Question-Answering in Large Language Models

Soyeon Kim, Jindong Wang, Xing Xie +1

Facts change over time, making it essential for Large Language Models (LLMs) to handle time-sensitive factual knowledge accurately and reliably. Although factual Time-Sensitive Que…

cs.AI2026

Talking with Tables for Better LLM Factual Data Interactions

Jio Oh, Geon Heo, Seungjun Oh +5

Large Language Models (LLMs) often struggle with requests related to information retrieval and data manipulation that frequently arise in real-world scenarios under multiple condit…

cs.LG2025

BPL: Bias-adaptive Preference Distillation Learning for Recommender System

SeongKu Kang, Jianxun Lian, Dongha Lee +6

Recommender systems suffer from biases that cause the collected feedback to incompletely reveal user preference. While debiasing learning has been extensively studied, they mostly…

cs.AI2025

Value Compass Benchmarks: A Platform for Fundamental and Validated Evaluation of LLMs Values

Jing Yao, Xiaoyuan Yi, Shitong Duan +8

As Large Language Models (LLMs) achieve remarkable breakthroughs, aligning their values with humans has become imperative for their responsible development and customized applicati…

cs.AI2025

General Scales Unlock AI Evaluation with Explanatory and Predictive Power

Lexin Zhou, Lorenzo Pacchiardi, Fernando Martínez-Plumed +23

Ensuring safe and effective use of AI requires understanding and anticipating its performance on novel tasks, from advanced scientific challenges to transformed workplace activitie…