5 papers
Temporal Dependencies in In-Context Learning: The Role of Induction Heads
Anooshka Bajaj, Deven Mahesh Mistry, Sahaj Singh Maini +3
Large language models (LLMs) exhibit strong in-context learning capabilities, but how they track and retrieve information from context remains underexplored. Drawing on the free re…
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…
On the origins, growth, and radiative efficiency of J0529-4351, reportedly the fastest-growing known black hole
Yash Aggarwal
SMSS J0521-4351 is reportedly the most luminous quasar known to date, and assuming a mean radiative efficiency of 0.1, it is inferred to be the fastest-growing black hole, accretin…
Direct Collapse Black Hole Candidates from Decaying Dark Matter
Yash Aggarwal, James B. Dent, Philip Tanedo +1
Injecting 1-13.6 eV photons into the early universe can suppress the molecular hydrogen abundance and alter the star formation history dramatically enough to produce direct collaps…
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…