activity
20242026
most citedARAG: Agentic Retrieval Augmented Generation for Personalized Recommendation

1 citations · 1 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2026

GridVQA-X: A Framework for Evaluating Multimodal Explainability Methods

Sujay Belsare, Sudarshan Nikhil, Sushant Kumar +2

With the increasing development of Vision-Language Models, it becomes imperative that their predictions are readily explainable to relevant stakeholders. However, the field of expl…

cs.AI2026

LLM-HYPER: Generative CTR Modeling for Cold-Start Ad Personalization via LLM-Based Hypernetworks

Luyi Ma, Wanjia Sherry Zhang, Zezhong Fan +10

On online advertising platforms, newly introduced promotional ads face the cold-start problem, as they lack sufficient user feedback for model training. In this work, we propose LL…

cs.AI2025

No-Human in the Loop: Agentic Evaluation at Scale for Recommendation

Tao Zhang, Kehui Yao, Luyi Ma +7

Evaluating large language models (LLMs) as judges is increasingly critical for building scalable and trustworthy evaluation pipelines. We present ScalingEval, a large-scale benchma…

cs.IR2025

MetaSynth: Multi-Agent Metadata Generation from Implicit Feedback in Black-Box Systems

Shreeranjani Srirangamsridharan, Ali Abavisani, Reza Yousefi Maragheh +4

Meta titles and descriptions strongly shape engagement in search and recommendation platforms, yet optimizing them remains challenging. Search engine ranking models are black box e…

cs.CL2025

GRACE: Generative Recommendation via Journey-Aware Sparse Attention on Chain-of-Thought Tokenization

Luyi Ma, Wanjia Zhang, Kai Zhao +15

Generative models have recently demonstrated strong potential in multi-behavior recommendation systems, leveraging the expressive power of transformers and tokenization to generate…

cs.IR2025★ 1 cited

ARAG: Agentic Retrieval Augmented Generation for Personalized Recommendation

Reza Yousefi Maragheh, Pratheek Vadla, Priyank Gupta +7

Retrieval-Augmented Generation (RAG) has shown promise in enhancing recommendation systems by incorporating external context into large language model prompts. However, existing RA…

cs.LG2025

Scalable Permutation-Aware Modeling for Temporal Set Prediction

Ashish Ranjan, Ayush Agarwal, Shalin Barot +1

Temporal set prediction involves forecasting the elements that will appear in the next set, given a sequence of prior sets, each containing a variable number of elements. Existing…

cs.CL2024

Thread Detection and Response Generation using Transformers with Prompt Optimisation

Kevin Joshua T, Arnav Agarwal, Shriya Sanjay +5

Conversational systems are crucial for human-computer interaction, managing complex dialogues by identifying threads and prioritising responses. This is especially vital in multi-p…