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From the 1 of 83 linked papers with an AI index.

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20242026
most citedAI-Assisted Peer Review at Scale: The AAAI-26 AI Review Pilot

1 citations · 1 across the 43 of their papers we have counts for

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cs.IR2026

R-Searcher: Calibrating Retrieval and Reasoning Boundaries for Agentic Search

Sheng Zhang, Junyi Li, Wenlin Zhang +6

Recent search agents for multi-hop reasoning often fail by either retrieving incomplete evidence or reasoning over irrelevant portions of the retrieved content, leading to a retrie…

cs.IR2026

RAGR: Review-Augmented Generative Recommendation

Yingyi Zhang, Junyi Li, Yejing Wang +8

Sequential recommendation (SR) is traditionally formulated as next-item prediction over chronological item interactions. Although recent generative recommendation (GR) methods intr…

cs.IR2026

MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search

Sheng Zhang, Junyi Li, Yingyi Zhang +7

Recent advances in large language models (LLMs) have scaled the potential for reasoning and agentic search, wherein models autonomously plan, retrieve, and reason over external kno…

cs.IR2026

Evoking User Memory: Personalizing LLM via Recollection-Familiarity Adaptive Retrieval

Yingyi Zhang, Junyi Li, Wenlin Zhang +8

Personalized large language models (LLMs) rely on memory retrieval to incorporate user-specific histories, preferences, and contexts. Existing approaches either overload the LLM by…

cs.IR2026

To Search or Not to Search: Aligning the Decision Boundary of Deep Search Agents via Causal Intervention

Wenlin Zhang, Kuicai Dong, Junyi Li +9

Deep search agents, which autonomously iterate through multi-turn web-based reasoning, represent a promising paradigm for complex information-seeking tasks. However, current agents…

cs.IR2025

Search-Based Interaction For Conversation Recommendation via Generative Reward Model Based Simulated User

Xiaolei Wang, Chunxuan Xia, Junyi Li +5

Conversational recommendation systems (CRSs) use multi-turn interaction to capture user preferences and provide personalized recommendations. A fundamental challenge in CRSs lies i…