1 citations · 1 across the 3 of their papers we have counts for
4 papers
CrEst: Credibility Estimation for Contexts in LLMs via Weak Supervision
Dyah Adila, Shuai Zhang, Boran Han +2
The integration of contextual information has significantly enhanced the performance of large language models (LLMs) on knowledge-intensive tasks. However, existing methods often o…
Effectively Steer LLM To Follow Preference via Building Confident Directions
Bingqing Song, Boran Han, Shuai Zhang +5
Having an LLM that aligns with human preferences is essential for accommodating individual needs, such as maintaining writing style or generating specific topics of interest. The m…
InsTALL: Context-aware Instructional Task Assistance with Multi-modal Large Language Models
Pha Nguyen, Sailik Sengupta, Girik Malik +2
The improved competence of generative models can help building multi-modal virtual assistants that leverage modalities beyond language. By observing humans performing multi-step ta…
QueryBuilder: Human-in-the-Loop Query Development for Information Retrieval
Hemanth Kandula, Damianos Karakos, Haoling Qiu +4
Frequently, users of an Information Retrieval (IR) system start with an overarching information need (a.k.a., an analytic task) and proceed to define finer-grained queries covering…