Defu Lian

AIR-Bench: Automated Heterogeneous Information Retrieval Benchmark

2024 · arXiv (Cornell University)

Evaluation plays a crucial role in the advancement of information retrieval (IR) models. However, current benchmarks, which are based on predefined domains and human-labeled data, face limitations in addressing evaluation needs for emerging domains both …

Reinforced Information Retrieval

2025 · arXiv (Cornell University)

While retrieval techniques are widely used in practice, they still face significant challenges in cross-domain scenarios. Recently, generation-augmented methods have emerged as a promising solution to this problem. These methods enhance raw queries by incorporating …

MIT: A Multi-Tower Information Transfer Framework Based on Hierarchical Task Relationship Modeling

2025

With the advancement of e-commerce platforms and online recommendation systems, conversion objectives have evolved from singular to diverse goals. To simultaneously enhance the performance of multiple conversion objectives, multi-task learning has become a classic solution. …

ReasonEmbed: Enhanced Text Embeddings for Reasoning-Intensive Document Retrieval

2026

In this paper, we introduce ReasonEmbed, a novel text embedding model developed for reasoning-intensive document retrieval.Our work includes three key technical contributions.First, we propose ReMixer, a new data synthesis method that overcomes the triviality problem …

Collaborative Knowledge Base Embedding for Recommender Systems

2016

Among different recommendation techniques, collaborative filtering usually suffer from limited performance due to the sparsity of user-item interactions. To address the issues, auxiliary information is usually used to boost the performance. Due to the rapid …

Neural Memory Streaming Recommender Networks with Adversarial Training

2018

With the increasing popularity of various social media and E-commerce platforms, large volumes of user behaviour data (e.g., user transaction data, rating and review data) are being continually generated at unprecedented and ever-increasing scales. It …

Geography-Aware Sequential Location Recommendation

2020

Sequential location recommendation plays an important role in many applications such as mobility prediction, route planning and location-based advertisements. In spite of evolving from tensor factorization to RNN-based neural networks, existing methods did not make …

A Survey on Session-based Recommender Systems

2021 · ACM Computing Surveys

Recommender systems (RSs) have been playing an increasingly important role for informed consumption, services, and decision-making in the overloaded information era and digitized economy. In recent years, session-based recommender systems (SBRSs) have emerged as a …

HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization

2022 · Proceedings of the ACM Web Conference 2022

In large-scale recommender systems, the user-item networks are generally scale-free or expand exponentially. For the representation of the user and item, the latent features (a.k.a, embeddings) depend on how well the embedding space matches the …