Papers by Vinayak Gupta

2 papers
PROPER Agents: Proactivity Driven Personalized Agents for Advancing Knowledge Gap Navigation (2026.findings-acl)

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Challenge: Current approaches to proactive assistance are anchored in what users express or can read, leading to unnecessary or mistimed interventions.
Approach: They propose a framework that explicitly models user-specific knowledge gaps in a controlled manner.
Outcome: The proposed framework improves on quality scores and win rates across multiple domains, achieving up to 84% gains in single-turn evaluation and consistent dominance in multiturn interactions.
Language Models Still Struggle to Zero-shot Reason about Time Series (2024.findings-emnlp)

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Challenge: Time series are critical for decision-making in fields like finance and healthcare.
Approach: They propose a framework for time series reasoning that includes formal tasks and a dataset of multi-scale time series paired with text captions across ten domains.
Outcome: The proposed framework combines formal tasks and a dataset of multi-scale time series paired with text captions across ten domains to examine whether language models achieve three forms of reasoning.

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