Papers by Deven Mahesh Mistry

2 papers
Emergence of Episodic Memory in Transformers: Characterizing Changes in Temporal Structure of Attention Scores During Training (2025.naacl-long)

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Challenge: Existing studies have shown that attention heads have a temporal induction property that allows them to learn and reproduce sequences of tokens.
Approach: They analyze attention heads and transformer outputs to examine in-context temporal biases . they find that transformer output has a tendency toward in-constext serial recall .
Outcome: The findings shed light on similarities and differences between LLMs and human memory and learning.
Beyond Semantics: How Temporal Biases Shapes Retrieval in Transformer and State-Space Models (2026.eacl-long)

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Challenge: In-context learning depends on what appears in the prompt and on when it appears.
Approach: They construct prompts with repeated anchor tokens and average their predictions over hundreds of random permutations of the intervening context.
Outcome: The proposed model predicts the same tokens over hundreds of permutations over time.

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