7 papers
AccurateRAG: A Framework for Building Accurate Retrieval-Augmented Question-Answering Applications
Linh The Nguyen, Chi Tran, Dung Ngoc Nguyen +3
We introduce AccurateRAG -- a novel framework for constructing high-performance question-answering applications based on retrieval-augmented generation (RAG). Our framework offers…
Improving Table Understanding with LLMs and Entity-Oriented Search
Thi-Nhung Nguyen, Hoang Ngo, Dinh Phung +2
Our work addresses the challenges of understanding tables. Existing methods often struggle with the unpredictable nature of table content, leading to a reliance on preprocessing an…
Planning for Success: Exploring LLM Long-term Planning Capabilities in Table Understanding
Thi-Nhung Nguyen, Hoang Ngo, Dinh Phung +2
Table understanding is key to addressing challenging downstream tasks such as table-based question answering and fact verification. Recent works have focused on leveraging Chain-of…
An approach to hummed-tune and song sequences matching
Loc Bao Pham, Huong Hoang Luong, Phu Thien Tran +3
Melody stuck in your head, also known as "earworm", is tough to get rid of, unless you listen to it again or sing it out loud. But what if you can not find the name of that song? I…
Who's Who: Large Language Models Meet Knowledge Conflicts in Practice
Quang Hieu Pham, Hoang Ngo, Anh Tuan Luu +1
Retrieval-augmented generation (RAG) methods are viable solutions for addressing the static memory limits of pre-trained language models. Nevertheless, encountering conflicting sou…
RecGPT: Generative Pre-training for Text-based Recommendation
Hoang Ngo, Dat Quoc Nguyen
We present the first domain-adapted and fully-trained large language model, RecGPT-7B, and its instruction-following variant, RecGPT-7B-Instruct, for text-based recommendation. Exp…
A Self-enhancement Multitask Framework for Unsupervised Aspect Category Detection
Thi-Nhung Nguyen, Hoang Ngo, Kiem-Hieu Nguyen +1
Our work addresses the problem of unsupervised Aspect Category Detection using a small set of seed words. Recent works have focused on learning embedding spaces for seed words and…