一作ICLR 2026Poster· Applications / Language, Speech and Dialog
Beyond Markovian Drifts: Action-Biased Geometric Walks with Memory for Personalized Summarization
Parthiv Chatterjee · Asish Batha · Tashvi patel · Sourish Dasgupta · Tanmoy Chakraborty
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Parthiv Chatterjee · Asish Batha · Tashvi patel · Sourish Dasgupta · Tanmoy Chakraborty
Parthiv Chatterjee · Asish Joel Batha · Sourish Dasgupta · Tanmoy Chakraborty
Document summarization becomes more challenging when summaries must reflect a user’s subjective interests in addition to document salience. SOTA Large Language Models (LLMs) show strong in-context summarization capabilities. Prior works report that simply prepending long and dynamically evolving...