6 citations · 6 across the 15 of their papers we have counts for
8 papers · 1 filter
GUI Exploration Lab: Enhancing Screen Navigation in Agents via Multi-Turn Reinforcement Learning
Haolong Yan, Yeqing Shen, Xin Huang +9
With the rapid development of Large Vision Language Models, the focus of Graphical User Interface (GUI) agent tasks shifts from single-screen tasks to complex screen navigation cha…
PrediQL: Automated Testing of GraphQL APIs with LLMs
Shaolun Liu, Sina Marefat, Omar Tsai +4
GraphQL's flexible query model and nested data dependencies expose APIs to complex, context-dependent vulnerabilities that are difficult to uncover using conventional testing tools…
SocioBench: Modeling Human Behavior in Sociological Surveys with Large Language Models
Jia Wang, Ziyu Zhao, Tingjuntao Ni +1
Large language models (LLMs) show strong potential for simulating human social behaviors and interactions, yet lack large-scale, systematically constructed benchmarks for evaluatin…
NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scale
NextStep Team, Chunrui Han, Guopeng Li +47
Prevailing autoregressive (AR) models for text-to-image generation either rely on heavy, computationally-intensive diffusion models to process continuous image tokens, or employ ve…
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…
Weak Supervision Techniques towards Enhanced ASR Models in Industry-level CRM Systems
Zhongsheng Wang, Sijie Wang, Jia Wang +3
In the design of customer relationship management (CRM) systems, accurately identifying customer types and offering personalized services are key to enhancing customer satisfaction…
Open Vision Reasoner: Transferring Linguistic Cognitive Behavior for Visual Reasoning
Yana Wei, Liang Zhao, Jianjian Sun +15
The remarkable reasoning capability of large language models (LLMs) stems from cognitive behaviors that emerge through reinforcement with verifiable rewards. This work investigates…
Slow Perception: Let's Perceive Geometric Figures Step-by-step
Haoran Wei, Youyang Yin, Yumeng Li +6
Recently, "visual o1" began to enter people's vision, with expectations that this slow-thinking design can solve visual reasoning tasks, especially geometric math problems. However…