collaborators

10 papers

cs.CL2026

Beyond Rubrics: Exploration-Guided Evaluation Skills for Reward Modeling

Xing Yue, Linjuan Wu, Daoxin Zhang +2

Open-ended reward modeling requires judges that can follow subtle, domain-specific preferences when verifiable answers are unavailable. Existing rubric-based methods often address…

cs.CL2026

Beyond Literal Translation: Evaluating Cultural Effectiveness in Social Media UGC

Linjuan Wu, Ruiqi Zhang, Xinze Lyu +7

Social media platforms enable large-scale cross-lingual communication, but translating user-generated content (UGC) remains challenging due to its informal style, cultural referenc…

cs.CL2026

A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAM Integration into Upcycled MoE

Hao Zhou, Tianhao Li, Zhijun Wang +6

Expanding Large Language Models~(LLMs) to new languages is a costly endeavor, demanding extensive Continued Pre-Training~(CPT) and data-intensive alignment. While recent data-free…

cs.CL2026

Language as a Latent Variable for Reasoning Optimization

Linjuan Wu, Haoran Wei, Jialong Tang +4

As LLMs reduce English-centric bias, a surprising trend emerges: non-English responses sometimes outperform English on reasoning tasks. We hypothesize that language functions as a…

cs.CL2026

Pause or Fabricate? Training Language Models for Grounded Reasoning

Yiwen Qiu, Linjuan Wu, Yizhou Liu +9

Large language models have achieved remarkable progress on complex reasoning tasks. However, they often implicitly fabricate information when inputs are incomplete, producing confi…

cs.CL2025

Enhancing LLM Language Adaption through Cross-lingual In-Context Pre-training

Linjuan Wu, Haoran Wei, Huan Lin +4

Large language models (LLMs) exhibit remarkable multilingual capabilities despite English-dominated pre-training, attributed to cross-lingual mechanisms during pre-training. Existi…