18 citations · 39 across the 12 of their papers we have counts for
17 papers
Evidence-Anchored Overdose Death Prediction from Death Investigation Reports
Raavi Gupta, Ziqing Yang, Karli R. Hochstatter +8
Confirmation of overdose deaths in the United States is often delayed due to the complexities of certifying drug-involved deaths. Death investigation reports represent a rich but u…
Fantastic Metrics and How to Find Them: Meta-Evaluating Metrics for Multi-lingual Style-Personalized Generation
Anubhav Jangra, Adrian de Wynter
Meta-evaluation of text generation metrics and LLM-judges is primarily conducted using metric-human correlations. However, prior work has shown that correlation is not an appropria…
DivAlgo: A systematic evaluation of algorithmic diversity for code generation models
Anubhav Jangra, Smaranda Muresan
Code generation models are actively being used in professional and educational settings. However, the competence of large language models (LLMs) to generate algorithmically diverse…
CREATE: Creativity Evaluation of VLMs using the Visual Remote Associates Test
Ziqing Yang, Anubhav Jangra, Smaranda Muresan
Vision language models (VLMs) are used in creative tasks such as visual storytelling, design ideation, art interpretation, and advertising. Yet we lack principled ways to measure t…
LLMs as Science Journalists: Supporting Early-stage Researchers in Communicating Their Science to the Public
Milad Alshomary, Grace Li, Anubhav Jangra +3
The scientific community needs tools that help early-stage researchers effectively communicate their findings and innovations to the public. Although existing general-purpose Large…
Designing and Evaluating Chain-of-Hints for Scientific Question Answering
Anubhav Jangra, Smaranda Muresan
LLMs are reshaping education, with students increasingly relying on them for learning. Implemented using general-purpose models, these systems are likely to give away the answers,…
Evaluating Style-Personalized Text Generation: Challenges and Directions
Anubhav Jangra, Bahareh Sarrafzadeh, Silviu Cucerzan +2
With the surge of large language models (LLMs) and their ability to produce customized output, style-personalized text generation--"write like me"--has become a rapidly growing are…
Navigating the Landscape of Hint Generation Research: From the Past to the Future
Anubhav Jangra, Jamshid Mozafari, Adam Jatowt +1
Digital education has gained popularity in the last decade, especially after the COVID-19 pandemic. With the improving capabilities of large language models to reason and communica…
TriviaHG: A Dataset for Automatic Hint Generation from Factoid Questions
Jamshid Mozafari, Anubhav Jangra, Adam Jatowt
Nowadays, individuals tend to engage in dialogues with Large Language Models, seeking answers to their questions. In times when such answers are readily accessible to anyone, the s…
Large Scale Multi-Lingual Multi-Modal Summarization Dataset
Yash Verma, Anubhav Jangra, Raghvendra Kumar +1
Significant developments in techniques such as encoder-decoder models have enabled us to represent information comprising multiple modalities. This information can further enhance…
A Survey on Medical Document Summarization
Raghav Jain, Anubhav Jangra, Sriparna Saha +1
The internet has had a dramatic effect on the healthcare industry, allowing documents to be saved, shared, and managed digitally. This has made it easier to locate and share import…
T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation
Anubhav Jangra, Preksha Nema, Aravindan Raghuveer
Unavailability of parallel corpora for training text style transfer (TST) models is a very challenging yet common scenario. Also, TST models implicitly need to preserve the content…
Multi-hop Question Answering
Vaibhav Mavi, Anubhav Jangra, Adam Jatowt
The task of Question Answering (QA) has attracted significant research interest for long. Its relevance to language understanding and knowledge retrieval tasks, along with the simp…
WIDAR -- Weighted Input Document Augmented ROUGE
Raghav Jain, Vaibhav Mavi, Anubhav Jangra +1
The task of automatic text summarization has gained a lot of traction due to the recent advancements in machine learning techniques. However, evaluating the quality of a generated…
A Survey on Multi-modal Summarization
Anubhav Jangra, Sourajit Mukherjee, Adam Jatowt +2
The new era of technology has brought us to the point where it is convenient for people to share their opinions over an abundance of platforms. These platforms have a provision for…
Semantic Extractor-Paraphraser based Abstractive Summarization
Anubhav Jangra, Raghav Jain, Vaibhav Mavi +2
The anthology of spoken languages today is inundated with textual information, necessitating the development of automatic summarization models. In this manuscript, we propose an ex…
Multi-Modal Summary Generation using Multi-Objective Optimization
Anubhav Jangra, Sriparna Saha, Adam Jatowt +1
Significant development of communication technology over the past few years has motivated research in multi-modal summarization techniques. A majority of the previous works on mult…