NNetNav WebArena data
NNetNav's WebArena-oriented browser-interaction data release, with separate training and test files.
已审阅并标注「数据生成」的研究与资产。
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NNetNav's WebArena-oriented browser-interaction data release, with separate training and test files.
Mobile-agent supervision from emulator and simulator trajectories, plus executable tasks with starting states and success checks for reinforcement learning.
GUI grounding pre-training data for OS-Atlas in desktop (Linux, macOS, Windows), mobile and web domains, with element boxes stored as relative left, top, right and bottom ratios.
Interaction-driven pipeline that synthesizes mobile and web GUI agent trajectories without human supervision or predefined tasks, via reverse task synthesis and a trajectory reward model.
Reverse-task-synthesis mobile trajectories released in separate AndroidControl and AndroidWorld training annotation files.
Released dataset used to train PC-Agent-E, linked by the official pipeline for refining human trajectories and synthesizing action reasoning.
Planner and action-executor training examples for WebArena-Lite and WebVoyager, with model-specific processed files and raw trajectory annotations.
Announced GUI trajectory synthesis resources for recovery from policy-induced errors; the inspected repository marks code and data releases as in preparation.
Cross-platform training data released with ScaleCUA, with grounding and navigation annotations for Ubuntu, Windows, macOS, Android, iPhone and web screenshots.
GUI screenshots paired with localization instructions and targets, including absent-target examples; image access is gated under publisher terms.
Annotation files, task recipes, and image manifests for ScreenRef; screenshots reside in the separately gated image repository.
7,496 desktop grounding examples built from OmniAct screenshots, with annotations rewritten by GPT-4o to describe element appearance, spatial relations and function.
Web-interface grounding examples with instructions, element boxes and points, paired with a separately packaged screenshot archive.
Gated web grounding training data for UGround in Web-Hybrid and Web-Direct subsets, with a bounding-box version whose coordinates are normalized to 0-999.
Mobile GUI reward annotations released for training UI-Genie’s trajectory-assessment model.
Synthetic mobile GUI trajectory supervision and screenshots released with the UI-Genie agent-training pipeline.
Treats grounding instructions as multiple reasoning perspectives, releasing a data pipeline, training code and UI-Ins-7B and 32B models trained by SFT on synthesized instructions, then RL.
The released mobile training subset for the original UI-R1 3B model, with action annotations and individual screenshot files.
A public example subset of the UI-S1 mobile training data, packaged as JSONL annotations and Parquet images.
Web-task context, starting observations and action history paired with structured checklists and subgoal analyses for checklist generation.
Windows tray utility that records primary-display screenshots, keyboard key codes and mouse events as local JPEG and JSON files for training-data collection.
Trajectory collection and revision utilities that use tree search and model-guided critique to train agents to recover from mistakes, including WebShop tasks.
Generates synthetic computer-use tasks and records trajectories in OSWorld desktop environments and InSTA browser environments.
An Android automation implementation that builds app documentation from exploration traces and evaluates language-model-generated execution code in emulator workflows.
Data-generation, fine-tuning and evaluation utilities for teaching small language models to invoke Android intents through predefined functions.
Structured website-exploration and data-processing code that revisits discovered pages, proposes tasks and collects trajectories for web-agent fine-tuning.
Code for screenshot grounding through supervised training, teacher-guided distillation, reinforcement learning, and benchmark evaluation.
Released data-synthesis and evaluation scripts that distill planning and causal GUI knowledge into text for mid-training mobile interface agents.
A desktop trajectory-generation framework that moves from stochastic GUI exploration to inferred goals and multi-stage task completion, with retrospective reasoning annotations.
Android GUI-agent adaptation framework combining app exploration, generated curricula and rollout feedback with hint-conditioned step-level GRPO; the documented public training path targets Qwen3-VL-8B.
Collects and labels browser-exploration trajectories for agent training, with code for data processing, fine-tuning, and web evaluation.
Tools for refining and augmenting human computer-use trajectories, preparing supervised training data, and deploying a native PC-Agent-E scaffold.
A web-agent framework that separates high-level planning from action execution, with replanning and synthetic planner-data generation components.
A browser-agent training system that proposes tasks, collects visual interaction trajectories, and uses automated evaluation to drive policy improvement.
Computer-use training framework with VeriGen task synthesis, adaptive rollout sampling, and visual-context segmentation.
A web-agent framework that explores sites, synthesizes reusable interaction APIs and builds a skill library for later tasks.
Research code and linked models for step-verified computer-use training; the current repository describes STEVE-R1 and its trajectory releases.
Training configurations, preprocessing and inference examples for tutorial-trained GUI models, with a LLaMA-Factory fine-tuning workflow and screenshot-grounding interfaces.
Framework for generating GUI trajectories through tree-structured exploration and verification.
Synthesizes visual UI defects from mobile screenshots and Android layout metadata to support GUI-testing experiments.
Training and evaluation code for a mobile-agent framework that iteratively generates trajectories using agent and reward-model feedback.
Component for web-agent trajectory collection, supervised-data preparation and world-model-based trajectory synthesis.
Training pipeline that evolves web tasks from prior attempts and uses an outcome reward model to refine browser policies.
Collects human GUI demonstrations and inspects multimodal evidence to derive reusable agent workflow skills.
Online RL framework for GUI agents in which VLMs generate the training tasks and judge success from trajectory screenshots, with OSWorld and AndroidLab checkpoints trained from UI-TARS-7B-DPO.
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