A survey that categorizes RIR benchmarks by domain and modality, proposes a taxonomy for integrating reasoning into retrieval pipelines, and outlines key challenges.
Kuaisar: A unified search and recommendation dataset
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
years
2026 4verdicts
UNVERDICTED 4roles
background 2polarities
background 2representative citing papers
Receipt Replay OOD is a new small benchmark for evaluating screen replay detection robustness under domain shift using receipt images as proxies for identity documents.
CVA aggregates frozen VFM embeddings via latent reasoning to create compact video embeddings for efficient micro-video recommendation, delivering consistent performance gains and orders-of-magnitude efficiency improvements.
PRISM improves e-commerce search robustness by modeling preference-relevance interactions via preference rectification, LLM-driven semantic anchoring with prototypes, and preference-conditioned evidence routing.
citing papers explorer
-
A Survey of Reasoning-Intensive Retrieval: Progress and Challenges
A survey that categorizes RIR benchmarks by domain and modality, proposes a taxonomy for integrating reasoning into retrieval pipelines, and outlines key challenges.
-
Receipt Replay OOD: A Small Benchmark for Screen Replay Detection Under Domain Shift
Receipt Replay OOD is a new small benchmark for evaluating screen replay detection robustness under domain shift using receipt images as proxies for identity documents.
-
Compressed Video Aggregator: Content-driven Module for Efficient Micro-Video Recommendation
CVA aggregates frozen VFM embeddings via latent reasoning to create compact video embeddings for efficient micro-video recommendation, delivering consistent performance gains and orders-of-magnitude efficiency improvements.
-
PRISM: Refracting the Entangled User Behavior Space for E-Commerce Search
PRISM improves e-commerce search robustness by modeling preference-relevance interactions via preference rectification, LLM-driven semantic anchoring with prototypes, and preference-conditioned evidence routing.