activity
20212025
most citedFLUTE: Figurative Language Understanding through Textual Explanations

7 citations · 20 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2025

VideoNorms: Benchmarking Cultural Awareness of Video Language Models

Nikhil Reddy Varimalla, Yunfei Xu, Meng Fan Wang +2

As Video Large Language Models (VideoLLMs) are deployed globally, it is important to assess their ability to reason across cultural contexts. To advance cultural norm awareness eva…

cs.CL2025

Death of the Novel(ty): Beyond n-Gram Novelty as a Metric for Textual Creativity

Arkadiy Saakyan, Najoung Kim, Smaranda Muresan +1

N-gram novelty is widely used to evaluate language models' ability to generate text outside of their training data. More recently, it has also been adopted as a metric for measurin…

cs.CL2024

Understanding Figurative Meaning through Explainable Visual Entailment

Arkadiy Saakyan, Shreyas Kulkarni, Tuhin Chakrabarty +1

Large Vision-Language Models (VLMs) have demonstrated strong capabilities in tasks requiring a fine-grained understanding of literal meaning in images and text, such as visual ques…

cs.CL2023

Learning to Follow Object-Centric Image Editing Instructions Faithfully

Tuhin Chakrabarty, Kanishk Singh, Arkadiy Saakyan +1

Natural language instructions are a powerful interface for editing the outputs of text-to-image diffusion models. However, several challenges need to be addressed: 1) underspecific…

cs.CL2023★ 1 cited

NormDial: A Comparable Bilingual Synthetic Dialog Dataset for Modeling Social Norm Adherence and Violation

Oliver Li, Mallika Subramanian, Arkadiy Saakyan +2

Social norms fundamentally shape interpersonal communication. We present NormDial, a high-quality dyadic dialogue dataset with turn-by-turn annotations of social norm adherences an…

cs.CL2023★ 1 cited

ICLEF: In-Context Learning with Expert Feedback for Explainable Style Transfer

Arkadiy Saakyan, Smaranda Muresan

While state-of-the-art large language models (LLMs) can excel at adapting text from one style to another, current work does not address the explainability of style transfer models.…

cs.CL2023★ 5 cited

I Spy a Metaphor: Large Language Models and Diffusion Models Co-Create Visual Metaphors

Tuhin Chakrabarty, Arkadiy Saakyan, Olivia Winn +4

Visual metaphors are powerful rhetorical devices used to persuade or communicate creative ideas through images. Similar to linguistic metaphors, they convey meaning implicitly thro…

cs.CL2023★ 5 cited

Sociocultural Norm Similarities and Differences via Situational Alignment and Explainable Textual Entailment

Sky CH-Wang, Arkadiy Saakyan, Oliver Li +2

Designing systems that can reason across cultures requires that they are grounded in the norms of the contexts in which they operate. However, current research on developing comput…

cs.CL2022★ 7 cited

FLUTE: Figurative Language Understanding through Textual Explanations

Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh +1

Figurative language understanding has been recently framed as a recognizing textual entailment (RTE) task (a.k.a. natural language inference, or NLI). However, similar to classical…

cs.CL2021

Don't Go Far Off: An Empirical Study on Neural Poetry Translation

Tuhin Chakrabarty, Arkadiy Saakyan, Smaranda Muresan

Despite constant improvements in machine translation quality, automatic poetry translation remains a challenging problem due to the lack of open-sourced parallel poetic corpora, an…

cs.CL2021★ 1 cited

COVID-Fact: Fact Extraction and Verification of Real-World Claims on COVID-19 Pandemic

Arkadiy Saakyan, Tuhin Chakrabarty, Smaranda Muresan

We introduce a FEVER-like dataset COVID-Fact of claims concerning the COVID-19 pandemic. The dataset contains claims, evidence for the claims, and contradictory claims refu…