AI Research Lab
Explore the latest AI research papers, trending repositories, and technical articles from leading AI labs and the open source community.
Research Papers
View allAre We Ready for RL in Text-to-3D Generation? A Progressive Investigation
This paper is a systematic exploration of reinforcement learning for text-to-3D generation, dissecting reward design, RL algorithms, data scaling, and hierarchical optimization. The authors introduce a new benchmark (MME-3DR), propose Hi-GRPO for global-to-local 3D refinement, and build AR3D-R1—the first RL-tuned text-to-3D model that improves both global shape quality and fine-grained texture alignment.
OPV: Outcome-based Process Verifier for Efficient Long Chain-of-Thought Verification
OPV (Outcome-based Process Verifier) is a verifier model that inspects the rationale steps of long chains-of-thought via summarized outcomes, combining the strengths of outcome-based and process-based verification. Trained with an active learning loop, rejection fine-tuning, and RLVR, OPV reaches strong F1 on OPV-Bench and outperforms much larger models like Qwen3-Max-Preview at detecting reasoning errors.
Long-horizon Reasoning Agent for Olympiad-Level Mathematical Problem Solving
This work presents a long-horizon reasoning agent for Olympiad-level math that uses an Outcome-based Process Verifier (OPV) to supervise and clean up very long chains-of-thought. By summarizing and checking reasoning segments rather than only final answers, and training OPV via iterative active learning and RLVR, the system achieves new SOTA on a held-out benchmark while reducing annotation cost.
T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and Playground
T-pro 2.0 is an open-weight Russian large language model focused on hybrid reasoning: it can answer directly or emit explicit reasoning traces, and it’s optimized for low-latency inference via speculative decoding. Alongside the model, the authors release a Russian instruction corpus, a math benchmark, and an EAGLE-based inference stack, making it a practical foundation for Russian-language reasoning applications.
Memory in the Age of AI Agents
A substantial survey that systematizes the fast-growing literature on ‘agent memory’—how agentic LLM systems store, retrieve, and evolve information over time. It proposes a taxonomy across forms (token, parametric, latent), functions (factual, experiential, working) and dynamics, and catalogs existing benchmarks and frameworks. If you’re building agent systems with nontrivial memory, this is quickly becoming the reference map of the territory.
ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding
ReFusion is a masked diffusion model for text that decodes in parallel over contiguous ‘slots’ instead of individual tokens. By combining diffusion-based planning with autoregressive infilling, it recovers much of the quality of strong autoregressive LLMs while massively speeding up generation and allowing KV-cache reuse. This is one of the more serious attempts to rethink LLM decoding beyond the usual left-to-right paradigm.
Trending Repositories
View allstable-diffusion-webui
stable-diffusion-webui by AUTOMATIC1111 is the de facto standard local web interface for Stable Diffusion, providing a massive feature set—txt2img, img2img, inpainting/outpainting, upscaling, LoRA/embeddings support, training utilities, and a huge extension ecosystem—on top of consumer GPUs. If you’re doing any kind of image generation or fine-tuning with Stable Diffusion in a local or lab environment, this is usually the first tool people reach for and the one most community workflows target. ([github.com](https://github.com/AUTOMATIC1111/stable-diffusion-webui?utm_source=openai))
openai/codex
A lightweight coding agent that runs directly in your terminal, wiring OpenAI models into a loop that edits files, runs tests, and applies patches. Compared to IDE plugins, it’s closer to a shell-native ‘pair programmer’ that can operate on entire repos and workflows. Given its rapid adoption and tight integration with existing CLIs, it’s poised to become a reference design for terminal-first code agents.
simstudioai/sim
A full-stack platform for visually building, running, and deploying AI agent workflows. Provides a canvas for wiring together agents, tools, vector stores, and orchestrations, with both cloud-hosted and self-hosted (Docker/Ollama) options and strong Copilot integration. It effectively turns ‘agent graphs’ into a first-class artifact, which is where a lot of production LLM work is heading.
dify
A very popular production-ready platform for building agentic workflows and applications, with UI, orchestration, and deployment all in one. Given its star growth, it’s becoming a de facto choice for many teams moving beyond simple RAG bots. ([github.com](https://github.com/trending?since=daily))
thedotmack/claude-mem
A Claude Code plugin that logs your coding sessions, compresses them with Claude via the agent SDK, and feeds back relevant context into future sessions. In practice it acts like a persistent, AI-managed memory of your projects, making the assistant far more ‘aware’ of the codebase and past conversations. It’s a concrete, production-friendly take on the “long-term memory for coding agents” idea.
CopilotKit
React UI components plus backend infrastructure for building in-app AI copilots, chatbots, and agentic workflows. It’s becoming a go-to choice if you want "agentic frontends" without wiring everything from scratch. ([github.com](https://github.com/trending?since=daily))
Technical Articles
View allSynthID Detector: Identify content made with Google's AI tools
Google announces SynthID Detector, a web portal that lets you upload images, audio, video, or text generated with Google AI tools and automatically checks for imperceptible SynthID watermarks, highlighting which parts of the content are likely watermarked. For developers and media teams, it’s a turnkey authenticity check for content produced with models like Gemini, Imagen, Lyria, and Veo, designed to plug into editorial and trust-&-safety workflows. ([blog.google](https://blog.google/technology/ai/google-synthid-ai-content-detector/))
The new ChatGPT Images is here
OpenAI announces a new image generation model powering ChatGPT’s ‘Images’ experience, with a focus on more precise edits, better consistency across parts of an image, and finer control over style. The post walks through examples like detailed object editing and iterative refinement inside the chat UI, positioning images as a first-class modality alongside text and code. For developers, it signals that OpenAI’s flagship image stack is now accessible through a very productized, user-facing interface.