18 citations · 23 across the 14 of their papers we have counts for
14 papers
SPIKE-RL: Video-LLMs meet Bayesian Surprise
Sahithya Ravi, Aditya Chinchure, Raymond T. Ng +2
Real-world videos often show routine activities punctuated by memorable, surprising events. However, most Video-LLMs process videos by sampling frames uniformly, likely missing cri…
Out of Sight, Not Out of Context? Egocentric Spatial Reasoning in VLMs Across Disjoint Frames
Sahithya Ravi, Gabriel Sarch, Vibhav Vineet +2
An embodied AI assistant operating on egocentric video must integrate spatial cues across time - for instance, determining where an object A, glimpsed a few moments ago lies relati…
Grounding Task Assistance with Multimodal Cues from a Single Demonstration
Gabriel Sarch, Balasaravanan Thoravi Kumaravel, Sahithya Ravi +2
A person's demonstration often serves as a key reference for others learning the same task. However, RGB video, the dominant medium for representing these demonstrations, often fai…
Black Swan: Abductive and Defeasible Video Reasoning in Unpredictable Events
Aditya Chinchure, Sahithya Ravi, Raymond Ng +3
The commonsense reasoning capabilities of vision-language models (VLMs), especially in abductive reasoning and defeasible reasoning, remain poorly understood. Most benchmarks focus…
CulturalBench: A Robust, Diverse, and Challenging Cultural Benchmark by Human-AI CulturalTeaming
Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin +8
Robust, diverse, and challenging cultural knowledge benchmarks are essential for measuring our progress towards making LMs that are helpful across diverse cultures. We introduce Cu…
From Local Concepts to Universals: Evaluating the Multicultural Understanding of Vision-Language Models
Mehar Bhatia, Sahithya Ravi, Aditya Chinchure +2
Despite recent advancements in vision-language models, their performance remains suboptimal on images from non-western cultures due to underrepresentation in training datasets. Var…
CulturalTeaming: AI-Assisted Interactive Red-Teaming for Challenging LLMs' (Lack of) Multicultural Knowledge
Yu Ying Chiu, Liwei Jiang, Maria Antoniak +7
Frontier large language models (LLMs) are developed by researchers and practitioners with skewed cultural backgrounds and on datasets with skewed sources. However, LLMs' (lack of)…
Empowering Air Travelers: A Chatbot for Canadian Air Passenger Rights
Maksym Taranukhin, Sahithya Ravi, Gabor Lukacs +2
The Canadian air travel sector has seen a significant increase in flight delays, cancellations, and other issues concerning passenger rights. Recognizing this demand, we present a…
Small But Funny: A Feedback-Driven Approach to Humor Distillation
Sahithya Ravi, Patrick Huber, Akshat Shrivastava +4
The emergence of Large Language Models (LLMs) has brought to light promising language generation capabilities, particularly in performing tasks like complex reasoning and creative…
CASE: Commonsense-Augmented Score with an Expanded Answer Space
Wenkai Chen, Sahithya Ravi, Vered Shwartz
LLMs have demonstrated impressive zero-shot performance on NLP tasks thanks to the knowledge they acquired in their training. In multiple-choice QA tasks, the LM probabilities are…
COMET-M: Reasoning about Multiple Events in Complex Sentences
Sahithya Ravi, Raymond Ng, Vered Shwartz
Understanding the speaker's intended meaning often involves drawing commonsense inferences to reason about what is not stated explicitly. In multi-event sentences, it requires unde…
What happens before and after: Multi-Event Commonsense in Event Coreference Resolution
Sahithya Ravi, Chris Tanner, Raymond Ng +1
Event coreference models cluster event mentions pertaining to the same real-world event. Recent models rely on contextualized representations to recognize coreference among lexical…
VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge
Sahithya Ravi, Aditya Chinchure, Leonid Sigal +2
There has been a growing interest in solving Visual Question Answering (VQA) tasks that require the model to reason beyond the content present in the image. In this work, we focus…
OpenML-Python: an extensible Python API for OpenML
Matthias Feurer, Jan N. van Rijn, Arlind Kadra +6
OpenML is an online platform for open science collaboration in machine learning, used to share datasets and results of machine learning experiments. In this paper we introduce Open…