collaborators

5 papers

cs.AI2026

PEEK: Context Map as an Orientation Cache for Long-Context LLM Agents

Zhuohan Gu, Qizheng Zhang, Omar Khattab +1

Large language model (LLM) agents increasingly operate over long and recurring external contexts, like document corpora and code repositories. Across invocations, existing approach…

cs.DB2026

SAGE: Selective Attention-Guided Extraction for Token-Efficient Document Indexing

Xinzhi Wang, Peter Baile Chen, Gerardo Vitagliano +5

Large language models with long context windows can answer complex questions directly from full-length academic, technical, and policy documents, but passing entire documents is of…

cs.DB2026

Abacus: A Cost-Based Optimizer for Semantic Operator Systems

Matthew Russo, Chunwei Liu, Sivaprasad Sudhir +4

LLMs enable an exciting new class of data processing applications over large collections of unstructured documents. Several new programming frameworks have enabled developers to bu…

cs.CL2025

CONCUR: A Framework for Continual Constrained and Unconstrained Routing

Peter Baile Chen, Weiyue Li, Dan Roth +3

AI tasks differ in complexity and are best addressed with different computation strategies (e.g., combinations of models and decoding methods). Hence, an effective routing system t…

cs.CL2025

Log-Augmented Generation: Scaling Test-Time Reasoning with Reusable Computation

Peter Baile Chen, Yi Zhang, Dan Roth +3

While humans naturally learn and adapt from past experiences, large language models (LLMs) and their agentic counterparts struggle to retain reasoning from previous tasks and apply…