Trending Research
Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learning
volcengine/verl
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We propose Rec-R1, a general reinforcement learning framework that bridges large language models (LLMs) with recommendation systems through closed-loop optimization.
Perception-R1: Pioneering Perception Policy with Reinforcement Learning
linkangheng/pr1
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In this work, we return to the fundamentals and explore the effects of RL on different perception tasks.
Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster
We study recent research advances that improve large language models through efficient pre-training and scaling, and open datasets and tools.
3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting
nv-tlabs/3dgrut
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3D Gaussian Splatting (3DGS) enables efficient reconstruction and high-fidelity real-time rendering of complex scenes on consumer hardware.
AssistanceZero: Scalably Solving Assistance Games
cassidylaidlaw/minecraft-building-assistance-game
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We present the first scalable approach to solving assistance games and apply it to a new, challenging Minecraft-based assistance game with over $10^{400}$ possible goals.
Docling Technical Report
DS4SD/docling
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This technical report introduces Docling, an easy to use, self-contained, MIT-licensed open-source package for PDF document conversion.
Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs
stanfordnlp/dspy
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To make this tractable, we factorize our problem into optimizing the free-form instructions and few-shot demonstrations of every module and introduce several strategies to craft task-grounded instructions and navigate credit assignment across modules.
VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model
om-ai-lab/vlm-r1
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Motivated by this observation, we investigate the extension of R1-style reinforcement learning to Vision-Language Models (VLMs), aiming to enhance their visual reasoning capabilities.
Do Large Language Models Need a Content Delivery Network?
lmcache/lmcache
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As the use of large language models (LLMs) expands rapidly, so does the range of knowledge needed to supplement various LLM queries.
