Stars
An open-source visual programming environment for battle-testing prompts to LLMs.
A web-based collaborative LaTeX editor
Official Implementation for EMNLP 2024 (main) "AgentReview: Exploring Academic Peer Review with LLM Agent."
Lightweight and Interpretable ML Model for Speech Emotion Recognition and Ambiguity Resolution (trained on IEMOCAP dataset)
Data Augmentation for Intent Classification with Off-the-Shelf Large Language Models is a ServiceNow Research project
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
A scalable asynchronous reinforcement learning implementation with in-flight weight updates.
A category wise collection of 200+ LLM survey papers.
A list of things related to Deep Research at one place
DoomArena is a Framework for Testing AI Agents Against Evolving Security Threats
FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI…
Code for LitLLMs, LLMs for Literature Review: Are we there yet? (TMLR 2025)
Unsloth Studio is a web UI for training and running open models like Gemma 4, Qwen3.5, DeepSeek, gpt-oss locally.
StarVector is a foundation model for SVG generation that transforms vectorization into a code generation task. Using a vision-language modeling architecture, StarVector processes both visual and te…
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Production-tested AI infrastructure tools for efficient AGI development and community-driven innovation
Wan: Open and Advanced Large-Scale Video Generative Models
Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.
[ICLR'25] ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
A high-throughput and memory-efficient inference and serving engine for LLMs
Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.
Code for 'LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders'
[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments