6 citations · 11 across the 12 of their papers we have counts for
11 papers · 1 filter
Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models
Shachi H Kumar, Saurav Sahay, Sahisnu Mazumder +6
Large Language Models (LLMs) have excelled at language understanding and generating human-level text. However, even with supervised training and human alignment, these LLMs are sus…
Zero-shot Conversational Summarization Evaluations with small Large Language Models
Ramesh Manuvinakurike, Saurav Sahay, Sangeeta Manepalli +1
Large Language Models (LLMs) exhibit powerful summarization abilities. However, their capabilities on conversational summarization remains under explored. In this work we evaluate…
Sample Efficient Multimodal Semantic Augmentation for Incremental Summarization
Sumanta Bhattacharyya, Ramesh Manuvinakurike, Sahisnu Mazumder +1
In this work, we develop a prompting approach for incremental summarization of task videos. We develop a sample-efficient few-shot approach for extracting semantic concepts as an i…
Position Matters! Empirical Study of Order Effect in Knowledge-grounded Dialogue
Hsuan Su, Shachi H Kumar, Sahisnu Mazumder +7
With the power of large pretrained language models, various research works have integrated knowledge into dialogue systems. The traditional techniques treat knowledge as part of th…
Human in the loop approaches in multi-modal conversational task guidance system development
Ramesh Manuvinakurike, Sovan Biswas, Giuseppe Raffa +6
Development of task guidance systems for aiding humans in a situated task remains a challenging problem. The role of search (information retrieval) and conversational systems for t…
Controllable Response Generation for Assistive Use-cases
Shachi H Kumar, Hsuan Su, Ramesh Manuvinakurike +2
Conversational agents have become an integral part of the general population for simple task enabling situations. However, these systems are yet to have any social impact on the di…
Estimating Subjective Crowd-Evaluations as an Additional Objective to Improve Natural Language Generation
Jakob Nyberg, Ramesh Manuvinakurike, Maike Paetzel-Prüsmann
Human ratings are one of the most prevalent methods to evaluate the performance of natural language processing algorithms. Similarly, it is common to measure the quality of sentenc…
"Can you say more about the location?" The Development of a Pedagogical Reference Resolution Agent
Maike Paetzel, Ramesh Manuvinakurike
In an increasingly globalized world, geographic literacy is crucial. In this paper, we present a collaborative two-player game to improve people's ability to locate countries on th…
A System for Automated Image Editing from Natural Language Commands
Jacqueline Brixey, Ramesh Manuvinakurike, Nham Le +3
This work presents the task of modifying images in an image editing program using natural language written commands. We utilize a corpus of over 6000 image edit text requests to al…
Towards Understanding End-of-trip Instructions in a Taxi Ride Scenario
Deepthi Karkada, Ramesh Manuvinakurike, Kallirroi Georgila
We introduce a dataset containing human-authored descriptions of target locations in an "end-of-trip in a taxi ride" scenario. We describe our data collection method and a novel an…
A Dialogue Annotation Scheme for Weight Management Chat using the Trans-Theoretical Model of Health Behavior Change
Ramesh Manuvinakurike, Sumanth Bharadwaj, Kallirroi Georgila
In this study we collect and annotate human-human role-play dialogues in the domain of weight management. There are two roles in the conversation: the "seeker" who is looking for w…