collaborators

6 papers

cs.AI2026

What Is a Skill Worth? Structure-Aware Shapley Valuation of Agent Skills

Tao Li, Junfeng Liu, Qinghua Zhao +5

Agent skills are increasingly optimized by automated feedback loops, producing long structured artifacts whose internal value remains unclear. We study skill valuation: assigning c…

cs.CL2026

Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters

Ailin Huang, Ang Li, Aobo Kong +213

We introduce Step 3.5 Flash, a sparse Mixture-of-Experts (MoE) model that bridges frontier-level agentic intelligence and computational efficiency. We focus on what matters most wh…

cs.CV2026

STEP3-VL-10B Technical Report

Ailin Huang, Chengyuan Yao, Chunrui Han +90

We present STEP3-VL-10B, a lightweight open-source foundation model designed to redefine the trade-off between compact efficiency and frontier-level multimodal intelligence. STEP3-…

cs.LG2025

SetAD: Semi-Supervised Anomaly Learning in Contextual Sets

Jianling Gao, Chongyang Tao, Xuelian Lin +2

Semi-supervised anomaly detection (AD) has shown great promise by effectively leveraging limited labeled data. However, existing methods are typically structured around scoring ind…

cs.CL2025

WebRouter: Query-specific Router via Variational Information Bottleneck for Cost-sensitive Web Agent

Tao Li, Jinlong Hu, Yang Wang +2

LLM-brained web agents offer powerful capabilities for web automation but face a critical cost-performance trade-off. The challenge is amplified by web agents' inherently complex p…

cs.LG2025

Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding

StepFun, :, Bin Wang +195

Large language models (LLMs) face low hardware efficiency during decoding, especially for long-context reasoning tasks. This paper introduces Step-3, a 321B-parameter VLM with hard…