Media Summary: Basilisk: Using Provenance Invariants to Automate Proofs of Undecidable Protocols Tony Nuda Zhang and Keshav Singh, ... Join this channel to get access to perks: Proudly sponsored by PyMC Labs: ... InfiniGen: Efficient Generative Inference of Large Language Models with Dynamic KV Cache Management Wonbeom Lee, Jungi ...
Osdi 2025 Bayesian Code Diffusion - Detailed Analysis & Overview
Basilisk: Using Provenance Invariants to Automate Proofs of Undecidable Protocols Tony Nuda Zhang and Keshav Singh, ... Join this channel to get access to perks: Proudly sponsored by PyMC Labs: ... InfiniGen: Efficient Generative Inference of Large Language Models with Dynamic KV Cache Management Wonbeom Lee, Jungi ... Joint Keynote Address: Accelerating Software Development: The LLM (R)evolution Emery Berger, University of Massachusetts ... WaferLLM: Large Language Model Inference at Wafer Scale Congjie He, Yeqi Huang, and Pei Mu, University of Edinburgh; ... Why Diffusion Models Don’t Memorize - NeurIPS 2025 Analysis
This talk was a part of Beyond the Prompt conference, hosted by and in London in 2026. Stay tuned for the ... Mirage: A Multi-Level Superoptimizer for Tensor Programs Mengdi Wu and Xinhao Cheng, Carnegie Mellon University; Shengyu ... DecDEC: A Systems Approach to Advancing Low-Bit LLM Quantization Yeonhong Park, Jake Hyun, Hojoon Kim, and Jae W. Lee, ... Compass: Encrypted Semantic Search with High Accuracy Jinhao Zhu, UC Berkeley; Liana Patel, Stanford University; Matei ... Every decentralized training run fails the same way: the model is technically impressive but nobody actually uses it. Eyad Gomaa ...
![[OSDI 2025] Bayesian Code Diffusion for Efficient Automatic Deep Learning Program Optimization](https://i.ytimg.com/vi/jlzJSoPiJRc/mqdefault.jpg)
