5 citations · 10 across the 13 of their papers we have counts for
13 papers
Towards Long Context Hallucination Detection
Siyi Liu, Kishaloy Halder, Zheng Qi +6
Large Language Models (LLMs) have demonstrated remarkable performance across various tasks. However, they are prone to contextual hallucination, generating information that is eith…
Exploration of Plan-Guided Summarization for Narrative Texts: the Case of Small Language Models
Matt Grenander, Siddharth Varia, Paula Czarnowska +3
Plan-guided summarization attempts to reduce hallucinations in small language models (SLMs) by grounding generated summaries to the source text, typically by targeting fine-grained…
Rethinking LLM Uncertainty: A Multi-Agent Approach to Estimating Black-Box Model Uncertainty
Yu Feng, Phu Mon Htut, Zheng Qi +7
Quantifying uncertainty in black-box LLMs is vital for reliable responses and scalable oversight. Existing methods, which gauge a model's uncertainty through evaluating self-consis…
Inference time LLM alignment in single and multidomain preference spectrum
Sadat Shahriar, Zheng Qi, Nikolaos Pappas +5
Aligning Large Language Models (LLM) to address subjectivity and nuanced preference levels requires adequate flexibility and control, which can be a resource-intensive and time-con…
Open Domain Question Answering with Conflicting Contexts
Siyi Liu, Qiang Ning, Kishaloy Halder +8
Open domain question answering systems frequently rely on information retrieved from large collections of text (such as the Web) to answer questions. However, such collections of t…
Characterizing and Measuring Linguistic Dataset Drift
Tyler A. Chang, Kishaloy Halder, Neha Anna John +4
NLP models often degrade in performance when real world data distributions differ markedly from training data. However, existing dataset drift metrics in NLP have generally not con…
A Weak Supervision Approach for Few-Shot Aspect Based Sentiment
Robert Vacareanu, Siddharth Varia, Kishaloy Halder +5
We explore how weak supervision on abundant unlabeled data can be leveraged to improve few-shot performance in aspect-based sentiment analysis (ABSA) tasks. We propose a pipeline a…
Task-Specific Embeddings for Ante-Hoc Explainable Text Classification
Kishaloy Halder, Josip Krapac, Alan Akbik +2
Current state-of-the-art approaches to text classification typically leverage BERT-style Transformer models with a softmax classifier, jointly fine-tuned to predict class labels of…
Enhancing Product Safety in E-Commerce with NLP
Kishaloy Halder, Josip Krapac, Dmitry Goryunov +6
Ensuring safety of the products offered to the customers is of paramount importance to any e- commerce platform. Despite stringent quality and safety checking of products listed on…
Instruction Tuning for Few-Shot Aspect-Based Sentiment Analysis
Siddharth Varia, Shuai Wang, Kishaloy Halder +7
Aspect-based Sentiment Analysis (ABSA) is a fine-grained sentiment analysis task which involves four elements from user-generated texts: aspect term, aspect category, opinion term,…
Modeling Information Need of Users in Search Sessions
Kishaloy Halder, Heng-Tze Cheng, Ellie Ka In Chio +3
Users issue queries to Search Engines, and try to find the desired information in the results produced. They repeat this process if their information need is not met at the first p…
Sentiment Analysis for Twitter : Going Beyond Tweet Text
Lahari Poddar, Kishaloy Halder, Xianyan Jia
Analysing sentiment of tweets is important as it helps to determine the users' opinion. Knowing people's opinion is crucial for several purposes starting from gathering knowledge a…
Properties of Farey Sequence and their Applications to Digital Image Processing
Soham Das, Kishaloy Halder, Sanjoy Pratihar +1
Farey sequence has been a topic of interest to the mathematicians since the very beginning of last century. With the emergence of various algorithms involving the digital plane in…