3 papers
cs.CL2025
Beyond Semantics: How Temporal Biases Shape Retrieval in Transformer and State-Space Models
Anooshka Bajaj, Deven Mahesh Mistry, Sahaj Singh Maini +2
In-context learning is governed by both temporal and semantic relationships, shaping how Large Language Models (LLMs) retrieve contextual information. Analogous to human episodic m…
q-bio.NC2025
Vision-language models learn the geometry of human perceptual space
Craig Sanders, Billy Dickson, Sahaj Singh Maini +2
In cognitive science and AI, a longstanding question is whether machines learn representations that align with those of the human mind. While current models show promise, it remain…
cs.LG2025
Emergence of Episodic Memory in Transformers: Characterizing Changes in Temporal Structure of Attention Scores During Training
Deven Mahesh Mistry, Anooshka Bajaj, Yash Aggarwal +2
We investigate in-context temporal biases in attention heads and transformer outputs. Using cognitive science methodologies, we analyze attention scores and outputs of the GPT-2 mo…