Text Data Augmentation Techniques in the Era of LLMs, A Function Calling Approach to Database Querying with LLMs, and More!

Vol.90 for Feb 03 - Feb 09, 2025

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

This week’s newsletter highlights the following research:

1. Adaptive Knowledge Retrieval through Markov Decision Processes, by Guan et al.

2. A Comprehensive Review of Text Data Augmentation for LLMs, from Chai et al.

3. A Function Calling Approach to Database Querying with LLMs, from Weaviate

4. A Two-Stage Framework for Integrating Language Models into CTR Prediction, from Huawei

5. A Two-Stage Framework for Knowledge Transfer from LLMs to Retrievers, from Korea University

6. Distilling Cross Encoder Knowledge into Efficient Dual Encoders, from IBM

7. Context-Aware Token Pruning for Memory-Efficient Dense Retrieval Systems, from Amazon

8. A Graph Foundation Model for Efficient Multi-hop Knowledge Retrieval, from Luo et al.

9. Enhancing Result Variety in Differentiable Search Indexes, from Walmart

10. A Scalable Transformer-Based Ranking Framework for Large-Scale Personalization, from LinkedIn