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From the 2 of 39 linked papers with an AI index.

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20242026
most citedLLM-Based Human-Agent Collaboration and Interaction Systems: A Survey

2 citations · 2 across the 22 of their papers we have counts for

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7 papers · 1 filter

cs.LG2026

Branching Policy Optimization: Sandbox-Native Language Agent Reinforcement Learning

Bowei He, Yankai Chen, Xiaokun Zhang +1

The paper proposes Branching Policy Optimization (BPO), a reinforcement learning method for large language model agents operating in deterministic, snapshottable sandboxes, which l…

cs.LG2026

Discrete Diffusion Models: A Unified Framework from Tokenization to Generation

Ye Yuan, Weien Li, Rui Song +20

The paper proposes a unified framework for discrete denoising diffusion models that ties together tokenization, vocabulary design, and generation methods, showing how existing appr…

cs.LG2026

Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption

Yankai Chen, Hanrong Zhang, Bowei He +2

Standard Set Representation Learning methods typically excel on curated data but often overlook the challenge of inference-time element corruption. This refers to scenarios where d…

cs.LG2026

The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project

Huamin Chen, Xunzhuo Liu, Bowei He +5

Over the past year, the vLLM Semantic Router project has released a series of work spanning: (1) core routing mechanisms -- signal-driven routing, context-length pool routing, rout…

cs.LG2025

SDrug: Bridging Protein Sequence and 3D Structure in Contrastive Representation Learning for Virtual Screening

Bowei He, Bowen Gao, Yankai Chen +5

Virtual screening (VS) is an essential task in drug discovery, focusing on the identification of small-molecule ligands that bind to specific protein pockets. Existing deep learnin…

cs.LG2025

DP-DGAD: A Generalist Dynamic Graph Anomaly Detector with Dynamic Prototypes

Jialun Zheng, Jie Liu, Jiannong Cao +4

Dynamic graph anomaly detection (DGAD) is essential for identifying anomalies in evolving graphs across domains such as finance, traffic, and social networks. Recently, generalist…