1 citations · 2 across the 8 of their papers we have counts for
8 papers
GRASP: GRanularity-Aware Search Policy for Agentic RAG
Varun Gandhi, Jaewook Lee, Shantanu Todmal +4
Agentic retrieval-augmented generation (RAG) extends static RAG by allowing language models to iteratively reason, generate search queries, retrieve evidence, and predict answers.…
Spinning Straw into Gold: Relabeling LLM Agent Trajectories in Hindsight for Successful Demonstrations
Zichao Li, Gang Wu, Zichao Wang +5
Large language model agents operate in partially observable, long-horizon settings where obtaining supervision remains a major bottleneck. We address this by utilizing a source of…
A Survey on LLM-based Conversational User Simulation
Bo Ni, Leyao Wang, Yu Wang +27
User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary medium of human communicatio…
Interview-Informed Generative Agents for Product Discovery: A Validation Study
Zichao Wang, Alexa Siu
Large language models (LLMs) have shown strong performance on standardized social science instruments, but their value for product discovery remains unclear. We investigate whether…
Reasoning-Based Personalized Generation for Users with Sparse Data
Bo Ni, Branislav Kveton, Samyadeep Basu +14
Large Language Model (LLM) personalization holds great promise for tailoring responses by leveraging personal context and history. However, real-world users usually possess sparse…
MLLM as a UI Judge: Benchmarking Multimodal LLMs for Predicting Human Perception of User Interfaces
Reuben A. Luera, Ryan Rossi, Franck Dernoncourt +12
In an ideal design pipeline, user interface (UI) design is intertwined with user research to validate decisions, yet studies are often resource-constrained during early exploration…
A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models
Zihao Lin, Samyadeep Basu, Mohammad Beigi +18
The rise of foundation models has transformed machine learning research, prompting efforts to uncover their inner workings and develop more efficient and reliable applications for…
On Mechanistic Circuits for Extractive Question-Answering
Samyadeep Basu, Vlad Morariu, Zichao Wang +4
Large language models are increasingly used to process documents and facilitate question-answering on them. In our paper, we extract mechanistic circuits for this real-world langua…