2 citations · 6 across the 14 of their papers we have counts for
10 papers · 1 filter
Understanding Cross-Domain Adaptation in Low-Resource Topic Modeling
Pritom Saha Akash, Kevin Chen-Chuan Chang
Topic modeling plays a vital role in uncovering hidden semantic structures within text corpora, but existing models struggle in low-resource settings where limited target-domain da…
ERU-KG: Efficient Reference-aligned Unsupervised Keyphrase Generation
Lam Thanh Do, Aaditya Bodke, Pritom Saha Akash +1
Unsupervised keyphrase prediction has gained growing interest in recent years. However, existing methods typically rely on heuristically defined importance scores, which may lead t…
Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models
Youan Cong, Pritom Saha Akash, Cheng Wang +1
We introduce the \textit{Extract-Refine-Retrieve-Read} (ERRR) framework, a novel approach designed to bridge the pre-retrieval information gap in Retrieval-Augmented Generation (RA…
Enhancing Short-Text Topic Modeling with LLM-Driven Context Expansion and Prefix-Tuned VAEs
Pritom Saha Akash, Kevin Chen-Chuan Chang
Topic modeling is a powerful technique for uncovering hidden themes within a collection of documents. However, the effectiveness of traditional topic models often relies on suffici…
Long-form Question Answering: An Iterative Planning-Retrieval-Generation Approach
Pritom Saha Akash, Kashob Kumar Roy, Lucian Popa +1
Long-form question answering (LFQA) poses a challenge as it involves generating detailed answers in the form of paragraphs, which go beyond simple yes/no responses or short factual…
Let the Pretrained Language Models "Imagine" for Short Texts Topic Modeling
Pritom Saha Akash, Jie Huang, Kevin Chen-Chuan Chang
Topic models are one of the compelling methods for discovering latent semantics in a document collection. However, it assumes that a document has sufficient co-occurrence informati…
Text Fact Transfer
Nishant Balepur, Jie Huang, Kevin Chen-Chuan Chang
Text style transfer is a prominent task that aims to control the style of text without inherently changing its factual content. To cover more text modification applications, such a…
Ask To The Point: Open-Domain Entity-Centric Question Generation
Yuxiang Liu, Jie Huang, Kevin Chen-Chuan Chang
We introduce a new task called *entity-centric question generation* (ECQG), motivated by real-world applications such as topic-specific learning, assisted reading, and fact-checkin…
Descriptive Knowledge Graph in Biomedical Domain
Kerui Zhu, Jie Huang, Kevin Chen-Chuan Chang
We present a novel system that automatically extracts and generates informative and descriptive sentences from the biomedical corpus and facilitates the efficient search for relati…
TopicAdapt- An Inter-Corpora Topics Adaptation Approach
Pritom Saha Akash, Trisha Das, Kevin Chen-Chuan Chang
Topic models are popular statistical tools for detecting latent semantic topics in a text corpus. They have been utilized in various applications across different fields. However,…