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Jaya Narain

3 accepted papers

2025

Do LLMs ``know'' internally when they follow instructions?

ICLR 2025poster

Instruction-following is crucial for building AI agents with large language models (LLMs), as these models must adhere strictly to user-provided constraints and guidelines. However, LLMs often fail to follow even simple and clear instructions. To improve instruction-following behavior and prevent u…

2025

Do LLMs estimate uncertainty well in instruction-following?

ICLR 2025poster

Large language models (LLMs) could be valuable personal AI agents across various domains, provided they can precisely follow user instructions. However, recent studies have shown significant limitations in LLMs' instruction-following capabilities, raising concerns about their reliability in high-sta…

2025

RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data

ICLR 2025poster

We present RelCon, a novel self-supervised Relative Contrastive learning approach for training a motion foundation model from wearable accelerometry sensors. First, a learnable distance measure is trained to capture motif similarity and domain-specific semantic information such as rotation invarianc…