Generating Synthetic Queries for Virtual Assistants using LLMs, Matryoshka Representations for Recommender Systems, and More!

Vol.56 for Jun 10 - Jun 16, 2024

Stay Ahead of the Curve with the Latest Advancements and Discoveries in Information Retrieval.

This week’s newsletter highlights the following research:

1. Leveraging Large Language Models for Synthetic Query Generation in Virtual Assistants, from Apple

2. Matryoshka Representations for Enhanced Recommender Systems, from HKBU

3. Towards Cost-Aware and Accurate Query Retrieval via Progressive LLM-Assisted Expansion, from UCR

4. In-context Learning vs. Fine-tuning: Evaluating LLM Adaptation for Diverse Dialogue Tasks, from UNITN

5. A Unified Framework for Text-to-Image Generation and Retrieval with Multimodal Large Language Models, from Qu et al.

6. Asynchronous Learning of User Representations for Large-Scale Recommendation, from Meta

7. A Comprehensive Survey for Bridging Generative AI and Industrial Recommenders, from Xu et al.

8. Leveraging Multi-Head Attention for Improved Retrieval Augmented Generation, from Besta et al.

9. Rectifying Unsuitable Recommendations without Retraining, from Lai et al.

10. An Efficient MLP-like Architecture for Sequential Recommendation, from Jian et al.