works on

From the 2 of 13 linked papers with an AI index.

activity
20242026
collaborators

13 papers

cs.CV2026

SeeSE3: Emergence of 3D Space in Vision Features

Caroline Chen, Sayna Ebrahimi, Fedor Kitashov +4

The paper examines whether vision foundation models implicitly encode the geometry of 3D Euclidean space, introducing probes such as a mutual neighborhood metric and a Poincaré Ada…

cs.LG2026

The Computational Basis of Confidence in Large Language Models

Dharshan Kumaran, Viorica Patraucean, Maks Ovsjanikov +3

The paper investigates what the confidence signal in large language models actually represents, showing that answer logits often act as monotonic readouts of a latent decision vari…

cs.CV2026

Unique Lives, Shared World: Learning from Single-Life Videos

Tengda Han, Sayna Ebrahimi, Dilara Gokay +8

We introduce the "single-life" learning paradigm, where we train a distinct vision model exclusively on egocentric videos captured by one individual. We leverage the multiple viewp…

cs.LG2026

Causal Evidence that Language Models use Confidence to Drive Behavior

Dharshan Kumaran, Nathaniel Daw, Simon Osindero +2

Metacognition -- assessing the quality of one's own cognitive performance -- guides adaptive behavior across species. Substantial research demonstrates that confidence signals can…

cs.CL2026

How do LLMs Compute Verbal Confidence

Dharshan Kumaran, Arthur Conmy, Federico Barbero +3

Verbal confidence -- prompting LLMs to state their confidence as a number or category -- is widely used to extract uncertainty estimates from black-box models. However, how LLMs in…

cs.LG2026

How LLMs Detect and Correct Their Own Errors: The Role of Internal Confidence Signals

Dharshan Kumaran, Viorica Patraucean, Simon Osindero +2

Large language models can detect their own errors and sometimes correct them without external feedback, but the underlying mechanisms remain unknown. We investigate this through th…