3 papers
cs.LG2026
Intrinsic Structure: Spectral Identifiability for Mechanistic Interpretability
Ashim Dhor, Pin-Yu Chen
Mechanistic interpretability explains models by identifying circuits inside them, but has no way to tell whether a circuit is a property of the model or an artifact of the method t…
cs.CV2026
Can Vision-Language Models Reason about AI Edits in Images?
Darsha Udayanga, Pin-Yu Chen, Payel Das +1
The paper explores training vision-language models with reinforcement learning to detect and localize AI-generated image edits, using reasoning traces and a lightweight segmentatio…
cs.AI2026
ITNet: A Learnable Integral Transform That Subsumes Convolution, Attention, and Recurrence
Ashim Dhor, Rasel Mondal, Pin-Yu Chen
Convolutional networks, recurrent networks, and transformers each encode different inductive biases -- locality, sequential memory, and content-dependent pairwise interaction -- an…