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From the 1 of 69 linked papers with an AI index.

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20242026
most citedEnterprise Sales Copilot: Enabling Real-Time AI Support with Automatic Information Retrieval in Live Sales Calls

1 citations · 1 across the 19 of their papers we have counts for

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cs.CL2026

VLAA-GUI: Knowing When to Stop, Recover, and Search, A Modular Framework for GUI Automation

Qijun Han, Haoqin Tu, Zijun Wang +11

Autonomous GUI agents face two fundamental challenges: early stopping, where agents prematurely declare success without verifiable evidence, and repetitive loops, where agents cycl…

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.CL2026

CoAct-1: Computer-using Multi-Agent System with Coding Actions

Linxin Song, Yutong Dai, Viraj Prabhu +9

Autonomous agents that operate computers via Graphical User Interfaces (GUIs) often struggle with efficiency and reliability on complex, long-horizon tasks. While augmenting these…

cs.CL2026

A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agents

Wei-Chieh Huang, Weizhi Zhang, Yueqing Liang +57

Research in artificial intelligence is shifting from model innovations and benchmark scores towards problem definition and rigorous real-world evaluation. As the field enters the "…

cs.CL2026

Prompt Optimization Via Diffusion Language Models

Shiyu Wang, Haolin Chen, Liangwei Yang +8

We propose a diffusion-based framework for prompt optimization that leverages Diffusion Language Models (DLMs) to iteratively refine system prompts through masked denoising. By con…

cs.CL2026

UNIDOC-BENCH: A Unified Benchmark for Document-Centric Multimodal RAG

Xiangyu Peng, Can Qin, Zeyuan Chen +3

Multimodal retrieval-augmented Generation (MM-RAG) is a key approach for applying large language models (LLMs) and agents to real-world knowledge bases, yet current evaluations are…