1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.AI2026★ 1 cited
XGrammar-2: Dynamic and Efficient Structured Generation Engine for Agentic LLMs
Linzhang Li, Yixin Dong, Guanjie Wang +3
Modern LLM agents increasingly rely on dynamic structured generation, such as tool calling and response protocols. Unlike traditional structured generation with static structures,…
cs.CL2025
XGrammar: Flexible and Efficient Structured Generation Engine for Large Language Models
Yixin Dong, Charlie F. Ruan, Yaxing Cai +4
The applications of LLM Agents are becoming increasingly complex and diverse, leading to a high demand for structured outputs that can be parsed into code, structured function call…
cs.CL2024
Assessing Bias in Metric Models for LLM Open-Ended Generation Bias Benchmarks
Nathaniel Demchak, Xin Guan, Zekun Wu +3
Open-generation bias benchmarks evaluate social biases in Large Language Models (LLMs) by analyzing their outputs. However, the classifiers used in analysis often have inherent bia…