latent state refinement 1recommendation systems 1recursive inference 1sequential recommendation 1user modeling 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.IR2026
ATLAS: Learning to Recommend Across Unseen Domains
Pervez Shaik, Prosenjit Biswas, Abhinav Thorat +2
Recommender systems remain domain-bound: a model trained on one interaction environment typically requires retraining or target-domain adaptation before it can operate on a new cat…
cs.IR2026
RecRec: Recursive Refinement for Sequential Recommendation
Pervez Shaik, Prosenjit Biswas, Abhinav Thorat +2
The paper introduces RecRec, a lightweight sequential recommendation model that iteratively refines a compact latent user state using a shared recursive module with an evidence-anc…
cs.CL2025
From What to Why: Thought-Space Recommendation with Small Language Models
Prosenjit Biswas, Pervez Shaik, Abhinav Thorat +2
Large Language Models (LLMs) have advanced recommendation capabilities through enhanced reasoning, but pose significant challenges for real-world deployment due to high inference c…