Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

SWE-Lego

Team
university
https://github.com/orgs/SWE-Lego
SWE-Lego
Activity Feed

AI & ML interests

We study code intelligence.

Recent Activity

tcftrees  authored a paper 3 days ago
MMFormalizer: Multimodal Autoformalization in the Wild
tcftrees  authored a paper 3 days ago
MMDeepResearch-Bench: A Benchmark for Multimodal Deep Research Agents
tcftrees  authored a paper 3 days ago
OVD: On-policy Verbal Distillation
View all activity

Papers

What Makes Interaction Trajectories Effective for Training Terminal Agents?

SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving

View all Papers

Chaofan Tao's profile pictureYuxin Jiang's profile pictureHaoli Bai's profile pictureJierun Chen's profile pictureRuoyu Wang's profile pictureElvinDu's profile pictureTao Yuan's profile pictureShaowei Wang's profile picturelixiaohui's profile picturesidi yang's profile picture
SWE-Lego 's papers 2
1

What Makes Interaction Trajectories Effective for Training Terminal Agents?

SWE-Lego SWE-Lego
7
Submitted by
Yuxin Jiang
24

SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving

SWE-Lego SWE-Lego
68 4
Company
TOS Privacy About Careers
Website
Models Datasets Spaces Pricing Docs