Foundations & trends in multimodal machine learning: Principles, challenges, and open questions
Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …
computer agents with intelligent capabilities such as understanding, reasoning, and learning …
Breaking common sense: Whoops! a vision-and-language benchmark of synthetic and compositional images
Weird, unusual, and uncanny images pique the curiosity of observers because they
challenge commonsense. For example, an image released during the 2022 world cup …
challenge commonsense. For example, an image released during the 2022 world cup …
Visit-bench: A benchmark for vision-language instruction following inspired by real-world use
We introduce VisIT-Bench (Visual InsTruction Benchmark), a benchmark for evaluation of
instruction-following vision-language models for real-world use. Our starting point is curating …
instruction-following vision-language models for real-world use. Our starting point is curating …
Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation
Abstract Chain-of-Thought (CoT) guides large language models (LLMs) to reason step-by-
step and can motivate their logical reasoning ability. While effective for logical tasks CoT is …
step and can motivate their logical reasoning ability. While effective for logical tasks CoT is …
FLUTE: Figurative language understanding through textual explanations
Figurative language understanding has been recently framed as a recognizing textual
entailment (RTE) task (aka natural language inference, or NLI). However, similar to classical …
entailment (RTE) task (aka natural language inference, or NLI). However, similar to classical …
How well do large language models perform on faux pas tests?
N Shapira, G Zwirn, Y Goldberg - Findings of the Association for …, 2023 - aclanthology.org
Motivated by the question of the extent to which large language models “understand” social
intelligence, we investigate the ability of such models to generate correct responses to …
intelligence, we investigate the ability of such models to generate correct responses to …
Memecap: A dataset for captioning and interpreting memes
Memes are a widely popular tool for web users to express their thoughts using visual
metaphors. Understanding memes requires recognizing and interpreting visual metaphors …
metaphors. Understanding memes requires recognizing and interpreting visual metaphors …
WinoGAViL: Gamified association benchmark to challenge vision-and-language models
While vision-and-language models perform well on tasks such as visual question
answering, they struggle when it comes to basic human commonsense reasoning skills. In …
answering, they struggle when it comes to basic human commonsense reasoning skills. In …
MacGyver: Are Large Language Models Creative Problem Solvers?
We explore the creative problem-solving capabilities of modern large language models
(LLMs) in a constrained setting. The setting requires circumventing a cognitive bias known in …
(LLMs) in a constrained setting. The setting requires circumventing a cognitive bias known in …
Probing the Creativity of Large Language Models: Can models produce divergent semantic association?
Large language models possess remarkable capacity for processing language, but it
remains unclear whether these models can further generate creative content. The present …
remains unclear whether these models can further generate creative content. The present …