Nishanth Sridhar Nakshatri — accepted AI-conference papers

2025

Constrained Decoding with Speculative Lookaheads

Nishanth Sridhar Nakshatri, Shamik Roy, Rajarshi Das, Suthee Chaidaroon, Leonid Boytsov, Rashmi Gangadharaiah

NAACL 2025long

Constrained decoding with lookahead heuristics (CDLH) is a highly effective method for aligning LLM generations to human preferences. However, the extensive lookahead roll-out operations for each generated token makes CDLH prohibitively expensive, resulting in low adoption in practice. In contrast,…

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2025

Talking Point based Ideological Discourse Analysis in News Events

Nishanth Sridhar Nakshatri, Nikhil Mehta, Siyi Liu, Sihao Chen, Daniel Hopkins, Dan Roth +1

ACL 2025finding

Analyzing ideological discourse even in the age of LLMs remains a challenge, as these models often struggle to capture the key elements that shape real-world narratives. Specifically, LLMs fail to focus on characteristic elements driving dominant discourses and lack the ability to integrate contextu…

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2023

Using LLM for Improving Key Event Discovery: Temporal-Guided News Stream Clustering with Event Summaries

Nishanth Sridhar Nakshatri, Siyi Liu, Sihao Chen, Dan Roth, Dan Goldwasser, Daniel Hopkins

EMNLP 2023short findings

Understanding and characterizing the discus- sions around key events in news streams is important for analyzing political discourse. In this work, we study the problem of identification of such key events and the news articles associated with those events from news streams. We propose a generic fram…

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