2 citations · 6 across the 14 of their papers we have counts for
14 papers
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…
RL-based Query Rewriting with Distilled LLM for online E-Commerce Systems
Duy A. Nguyen, Rishi Kesav Mohan, Van Yang +2
Query rewriting (QR) is a critical technique in e-commerce search, addressing the lexical gap between user queries and product descriptions to enhance search performance. Existing…
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…
ConTReGen: Context-driven Tree-structured Retrieval for Open-domain Long-form Text Generation
Kashob Kumar Roy, Pritom Saha Akash, Kevin Chen-Chuan Chang +1
Open-domain long-form text generation requires generating coherent, comprehensive responses that address complex queries with both breadth and depth. This task is challenging due t…
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…
Cascade Speculative Drafting for Even Faster LLM Inference
Ziyi Chen, Xiaocong Yang, Jiacheng Lin +3
Introduced to enhance the efficiency of large language model (LLM) inference, speculative decoding operates by having a smaller model generate a draft. A larger target model then r…
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,…
Exploring Variational Graph Auto-Encoders for Extract Class Refactoring Recommendation
Pritom Saha Akash, Kevin Chen-Chuan Chang
The code smell is a sign of design and development flaws in a software system that reduces the reusability and maintainability of the system. Refactoring is done as an ongoing prac…