Stanford AI Lab Papers at ICML 2026
StanfordAILab · x · 2026-07-11
Stanford AI Lab announced they will present the paper "Scale Dependent Data Duplication" on the closing day of ICML 2026, led by Joshua K92829 and Noam Levi.
They also mentioned having two papers accepted at the MemFM workshop focusing on "the impact of memorization on trustworthy foundation models." The second paper is the previously mentioned "Internal Data Repetition Destroys Language Models". The presentation is scheduled for July 11, 3:50–5:00 pm, Hall A.
More from Research
- Structural ensembles beat single predictions in TCR:pMHC generalization study — quaidmorris · 2026-07-22
- Structural ensembles, not single predictions, drive robust TCR:pMHC generalization — quaidmorris · 2026-07-22
- A 3D ray plot shows how hard this Jacobian counterexample is to read — moultano · 2026-07-22
- LLM leaderboards are now often measuring the harness too, Gary Marcus warns — GaryMarcus · 2026-07-22
- New paper defines self-state attacks, showing OS defenses leave four agent-memory cases indistinguishable — Justgototheeffinmoon · 2026-07-22
- Krea 2 users recommend a two-pass Clownshark sampler setup for sharper image details — listopalafoto · 2026-07-22