29 citations · 64 across the 17 of their papers we have counts for
6 papers · 1 filter
TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents
James Enouen, Hootan Nakhost, Sayna Ebrahimi +3
Large language models (LLMs) have attracted huge interest in practical applications given their increasingly accurate responses and coherent reasoning abilities. Given their nature…
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data
Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha +4
Text-to-SQL aims to automate the process of generating SQL queries on a database from natural language text. In this work, we propose "SQLPrompt", tailored to improve the few-shot…
Effective Large Language Model Adaptation for Improved Grounding and Citation Generation
Xi Ye, Ruoxi Sun, Sercan Ö. Arik +1
Large language models (LLMs) have achieved remarkable advancements in natural language understanding and generation. However, one major issue towards their widespread deployment in…
COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning
Chuizheng Meng, Yihe Dong, Sercan Ö. Arık +2
Estimation of temporal counterfactual outcomes from observed history is crucial for decision-making in many domains such as healthcare and e-commerce, particularly when randomized…
Search-Adaptor: Embedding Customization for Information Retrieval
Jinsung Yoon, Sercan O Arik, Yanfei Chen +1
Embeddings extracted by pre-trained Large Language Models (LLMs) have significant potential to improve information retrieval and search. Beyond the zero-shot setup in which they ar…
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)
Ruoxi Sun, Sercan Ö. Arik, Alex Muzio +8
Text-to-SQL, the process of translating natural language into Structured Query Language (SQL), represents a transformative application of large language models (LLMs), potentially…