Oopsla 25 Mini Batch Robustness

Oopsla 25 Mini Batch Robustness Information Guide

1. Introduction of Oopsla 25 Mini Batch Robustness
2. Main Features
3. Developments
4. Deep Dive
5. Conclusion

Introduction of Oopsla 25 Mini Batch Robustness

An Empirical Study of Bugs in the rustc Compiler (Video, OOPSLA2 2025) Zixi Liu, Yang Feng, Yunbo Ni, Shaohua Li, Xizhe Yin, ... The Simple Essence of Monomorphization (Video, OOPSLA1 2025) Matthew Lutze, Philipp Schuster, and Jonathan Immanuel ... I got GLM-5.2 — a 744-billion-parameter Mixture-of-Experts model with Deep Sparse Attention — to serve at its full native context ... In this video I want to test the Qwopus 3.6 27B Coder MTP model from Jackrong, is it as good as the base Qwen model?

Main Features

Developments

[ICFP/SPLASH'25] Orchid Plenary Ballroom - SPLASH OOPSLA (Oct 17th)

[ICFP/SPLASH'25] Orchid Small - SPLASH OOPSLA (Oct 18th)

[ICFP/SPLASH'25] Orchid East - SPLASH OOPSLA (Oct 18th)

[SPLASH'24] IBR West - OOPSLA (Oct 25th)

AI Agent 【Tau】 Unlocking 1 Million Tokens of Context for a 744B Model. Hidden Kernel Wall (and Fix)

Qwopus 3.6 27B Coder MTP coding challenges - 16GB Local LLM setup

The Wrong Batch Size Will Ruin Your Model

ISCA'25 - Session 5B - Hybe: GPU-NPU Hybrid System for Efficient LLM Inference with Million-Token Co

Deep Dive

Data is compiled from public records and verified media reports.

Last Updated: June 20, 2026

Conclusion

Disclaimer: Disclaimer: Details estimates are based on publicly available data, media reports, and financial analysis. Actual numbers may vary.