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20242026
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cs.CL2026

DeltaFlow: Noise-Adaptive Bidirectional Gated Delta Networks for Embedded Language Flows

Guangfu Guo, Xiaoqian Lu, Linsey Pang +4

Embedded Language Flows (ELF) rely primarily on full non-causal attention for iterative denoising, repeatedly incurring quadratic sequence-mixing cost at each sampling step. Gated…

cs.CL2026

CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?

Haolin Chen, Deon Metelski, Leon Qi +30

End-to-end automation of realistic healthcare operations stresses three capabilities underrepresented in current benchmarks: policy density, decisions must be grounded in a large l…

cs.CL2026

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels

Zhepeng Cen, Haolin Chen, Shiyu Wang +8

Large Language Models (LLMs) have achieved remarkable success through imitation learning on vast text corpora, but this paradigm creates a training-generation gap and limits robust…

cs.CL2025

Enterprise Deep Research: Steerable Multi-Agent Deep Research for Enterprise Analytics

Akshara Prabhakar, Roshan Ram, Zixiang Chen +5

As information grows exponentially, enterprises face increasing pressure to transform unstructured data into coherent, actionable insights. While autonomous agents show promise, th…

cs.CL2025

APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay

Akshara Prabhakar, Zuxin Liu, Ming Zhu +12

Training effective AI agents for multi-turn interactions requires high-quality data that captures realistic human-agent dynamics, yet such data is scarce and expensive to collect m…

cs.CL2024

xLAM: A Family of Large Action Models to Empower AI Agent Systems

Jianguo Zhang, Tian Lan, Ming Zhu +19

Autonomous agents powered by large language models (LLMs) have attracted significant research interest. However, the open-source community faces many challenges in developing speci…