ScienceToStartup
TrendsTopicsSavedArticlesChangelogCareersAbout

113 Cherry St #92768

Seattle, WA 98104-2205

Backed by Research Labs
All systems operational

Product

  • Dashboard
  • Workspace
  • Build Loop
  • Research Map
  • Trends
  • Topics
  • Articles

Enterprise

  • TTO Dashboard
  • Scout Reports
  • RFP Marketplace
  • API

Resources

  • All Resources
  • Benchmark
  • Database
  • Dataset
  • Calculator
  • Glossary
  • State Reports
  • Industry Index
  • Directory
  • Templates
  • Alternatives
  • Changelog
  • FAQ
  • Docs

Company

  • About
  • Careers
  • For Media
  • Privacy Policy
  • Legal
  • Contact

Community

  • Open Source
  • Community
ScienceToStartup

Copyright © 2026 ScienceToStartup. All rights reserved.

Privacy Policy|Legal
  1. Home
  2. Signal Canvas
  3. GUI-Libra: Training Native GUI Agents to Reason and Act with
← Back to Paper

GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL

Fresh1d ago
Export BriefOpen in Build LoopConnect with Author
View PDF ↗
Viability
0.0/10

Compared to this week’s papers

Evidence Receipt

Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 0

Proof: pending

Distribution: unknown

Source paper: GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL

PDF: https://arxiv.org/pdf/2602.22190v1

First buyer signal: unknown

Distribution channel: unknown

Starting…

Dimensions overall score 7.0

GitHub Code Pulse

No public code linked for this paper yet.

Claim map

Claim extraction is still pending for this paper. Check back after the next analysis run.

Competitive landscape

Competitor map is still being generated for this paper. Enable generation or check back soon.

Keep exploring

Builds On This
WebFactory: Automated Compression of Foundational Language Intelligence into Grounded Web Agents
Score 6.0down
Builds On This
GUI-CEval: A Hierarchical and Comprehensive Chinese Benchmark for Mobile GUI Agents
Score 4.0down
Builds On This
Native Reasoning Models: Training Language Models to Reason on Unverifiable Data
Score 6.0down
Prior Work
GUIDE: Resolving Domain Bias in GUI Agents through Real-Time Web Video Retrieval and Plug-and-Play Annotation
Score 7.0stable
Prior Work
UI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experience
Score 7.0stable
Prior Work
Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text
Score 7.0stable
Prior Work
GAIA: A Data Flywheel System for Training GUI Test-Time Scaling Critic Models
Score 7.0stable
Higher Viability
SecAgent: Efficient Mobile GUI Agent with Semantic Context
Score 8.0up

Startup potential card

Startup potential card preview
Share on XLinkedIn

BUILDER'S SANDBOX

Build This Paper

Use an AI coding agent to implement this research.

OpenAI Codex
OpenAI CodexAI Agent

Lightweight coding agent in your terminal.

Claude Code
Claude CodeAI Agent

Agentic coding tool for terminal workflows.

AntiGravity IDE
AntiGravity IDEScaffolding

AI agent mindset installer and workflow scaffolder.

Cursor
CursorIDE

AI-first code editor built on VS Code.

VS Code
VS CodeIDE

Free, open-source editor by Microsoft.

Recommended Stack

OpenAI APILLM API
Anthropic ClaudeLLM API
LangChainAgent Framework
CrewAIAgent Framework
AutoGenAgent Framework

Startup Essentials

Antigravity

AI Agent IDE

Render

Deploy Backend

Railway

Full-Stack Deploy

Supabase

Backend & Auth

Vercel

Deploy Frontend

Firebase

Google Backend

Hugging Face Hub

ML Model Hub

Banana.dev

GPU Inference

MVP Investment

$9K - $13K
6-10 weeks
Engineering
$8,000
Cloud Hosting
$240
LLM API Credits
$500
SaaS Stack
$300
Domain & Legal
$100

6mo ROI

1-2x

3yr ROI

10-25x

Automation tools have long sales cycles but high retention. Expect $5K MRR by 6mo, accelerating to $500K+ ARR at 3yr as enterprises adopt.

Talent Scout

R

Rui Yang

UIUC

Q

Qianhui Wu

Microsoft

Z

Zhaoyang Wang

UNC-Chapel Hill

Find Similar Experts

Native experts on LinkedIn & GitHub