3 papers
cs.LG2026
Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation
Callum Canavan, Aditya Shrivastava, Allison Qi +2
To steer language models towards truthful outputs on tasks which are beyond human capability, previous work has suggested training models on easy tasks to steer them on harder ones…
cs.LG2026
Abstractive Red-Teaming of Language Model Character
Nate Rahn, Allison Qi, Avery Griffin +3
We want language model assistants to conform to a character specification, which asserts how the model should act across diverse user interactions. While models typically follow th…
cs.LG2026
Chunky Post-Training: Data Driven Failures of Generalization
Seoirse Murray, Allison Qi, Timothy Qian +3
LLM post-training involves many diverse datasets, each targeting a specific behavior. But these datasets encode incidental patterns alongside intended ones: correlations between fo…