PRISM: trace an LLM's outputs back to training data in a single forward pass
juliusadml · x · 2026-10-06
PRISM (Prototype Language Models) is a family of language models designed to make next-token predictions traceable to the pre-training data in a single forward pass. The work will be presented at COLM Poster Session 1, aiming to make model outputs interpretable and auditable rather than black-box generation.
Related event: PRISM Traces LLM Outputs to Training Data in a Single Forward Pass(3 posts)→
More from Research
- Force Prompting: video generation models learn physics-based control signals — creatoroff · 2026-10-07
- MIT CSAIL's DREAM unifies image understanding and generation, ~10% faster — MIT_CSAIL · 2026-10-07
- E2S finetuning turns off-policy expert data into on-policy student samples via amortized sampling — Lianhuiq · 2026-10-06
- IdeaLens: a new detector that tries to tell whether a text's ideas came from a human or AI — MohitIyyer · 2026-10-06
- COLM 2026 paper acceptance statistics released — xwang_lk · 2026-10-06
- μDPad turns smartwatch PPG heart-rate sensors into a micro-gesture imaging array — cholz · 2026-10-06