ChildEval:WHEN LARGE LANGUAGE MODELS MEET CHILDREN'S PERSONALITIES (2026)
LLM-based chatbots are increasingly used as companions for young children. Yet nobody has systematically tested whether these models pick up on and respect a child's preferences. Existing personalization benchmarks mostly target adults, and child-focused ones cover only narrow aspects such as safety or style…
PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning (2026)
LLM translation trained with reinforcement learning (e.g., GRPO) suffers from two problems. Its Monte Carlo group baselines are noisy, and its huge output space rewards broad exploration but gives little signal for small local fixes. PEGRL addresses this by treating translation as a two-step workflow: a draft…
Soft Orthogonal Low-Rank Adaptation for Knowledge Sharing in Large Language Model Continual Learning (2026)
The paper addresses continual learning (CL) for large language models. Full retraining is too costly at this scale, and most existing CL methods focus only on preventing catastrophic forgetting, without exploiting knowledge that tasks could share. The authors first observe that better-performing CL models produce…

Co-authors here

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

Updated 1 November 2026