From the 2 of 7 linked papers with an AI index.
7 papers
Reasoning Errors Have a Region and a Direction in the Residual-Stream Trajectory of LLMs
Hamed Damirchi, Ignacio Meza De la Jara, Damith Ranasinghe +2
As language models are increasingly used for tasks that require verifiable reasoning, reliably distinguishing sound reasoning from flawed reasoning has become an important practica…
Level, Sharpness, and Corpus: Why Zero-Shot OOD Detector Rankings Do Not Transfer
Ignacio M. De la Jara, Cristian Rodriguez-Opazo, Stephen Gould +1
The paper shows that zero-shot out-of-distribution detector rankings do not reliably transfer across vision-language model deployments and proposes a detector-agnostic wrapper, the…
Representation Trajectories Matters: Complementary Evidence for OOD Detection and Image Classification
Ignacio M. De la Jara, Cristian Rodriguez-Opazo, Hamed Damirchi +2
The paper investigates how the step‑by‑step changes in a vision model’s internal representations (representation trajectories) can be used to improve out‑of‑distribution detection…
Vertical Fusion: Condensing Internal Representations for Robust ViT Classification
Francesco Di Salvo, Shyam Nandan Rai, Hamed Damirchi +4
Despite exposing rich intermediate representations, Vision Transformers (ViTs) are almost exclusively utilized as black-box feature extractors, where only the last layer is conside…
Truth as a Trajectory: What Internal Representations Reveal About Large Language Model Reasoning
Hamed Damirchi, Ignacio Meza De la Jara, Ehsan Abbasnejad +3
Existing explainability methods for Large Language Models (LLMs) typically treat hidden states as static points in activation space, assuming that correct and incorrect inferences…
An empirical study of the effect of video encoders on Temporal Video Grounding
Ignacio M. De la Jara, Cristian Rodriguez-Opazo, Edison Marrese-Taylor +1
Temporal video grounding is a fundamental task in computer vision, aiming to localize a natural language query in a long, untrimmed video. It has a key role in the scientific commu…