4 citations · 14 across the 32 of their papers we have counts for
5 papers · 1 filter
When and How Should an Agent Clarify? CIGAsk: Teaching LLMs to Clarify via Counterfactual Information Gain
Yunxiang Li, Xixin Wu, Helen Meng
Instruction-tuned LLMs faced with underspecified queries often commit to a single interpretation rather than ask for clarification, producing confidently wrong answers. In our expe…
How Many Pixels Is a Digit Worth? Place-Aware Coordinate Entropy for GUI Agent Confidence Estimation
Yunxiang Li, Xixin Wu, Helen Meng
GUI agents predict click coordinates as digit-token sequences, but standard text-LLM confidence estimation methods rank correct clicks from wrong ones only weakly. GUI-specific alt…
UniAudio 2.0: A Unified Audio Language Model with Text-Aligned Factorized Audio Tokenization
Dongchao Yang, Yuanyuan Wang, Dading Chong +3
We study two foundational problems in audio language models: (1) how to design an audio tokenizer that can serve as an intermediate representation for both understanding and genera…
MiLorE-SSL: Scaling Multilingual Capabilities in Self-Supervised Models without Forgetting
Jing Xu, Minglin Wu, Xueyuan Chen +2
Self-supervised learning (SSL) has greatly advanced speech representation learning, but multilingual SSL models remain constrained to languages encountered during pretraining. Retr…
TreePS-RAG: Tree-based Process Supervision for Reinforcement Learning in Agentic RAG
Tianhua Zhang, Kun Li, Junan Li +5
Agentic retrieval-augmented generation (RAG) formulates question answering as a multi-step interaction between reasoning and information retrieval, and has recently been advanced b…