3 citations · 6 across the 11 of their papers we have counts for
12 papers
A Deeper Analysis of Block-Sparse Featurizers
Alexandru-Iulius Jerpelea, Amith Ananthram
The recently introduced block-sparse featurizer (BSF; Fel et al., 2026) is similar to a sparse autoencoder (SAE), but its atomic unit is a small subspace (a block of directions) ra…
Does AI See like Art Historians? Interpreting How Vision Language Models Recognize Artistic Style
Marvin Limpijankit, Milad Alshomary, Yassin Oulad Daoud +9
VLMs have become increasingly proficient at a range of computer vision tasks, such as visual question answering and object detection. This includes increasingly strong capabilities…
PoSh: Using Scene Graphs To Guide LLMs-as-a-Judge For Detailed Image Descriptions
Amith Ananthram, Elias Stengel-Eskin, Lorena A. Bradford +7
While vision-language models (VLMs) have advanced into detailed image description, evaluation remains a challenge. Standard metrics (e.g. CIDEr, SPICE) were designed for short text…
Mining Contextualized Visual Associations from Images for Creativity Understanding
Ananya Sahu, Amith Ananthram, Kathleen McKeown
Understanding another person's creative output requires a shared language of association. However, when training vision-language models such as CLIP, we rely on web-scraped dataset…
Data Caricatures: On the Representation of African American Language in Pretraining Corpora
Nicholas Deas, Blake Vente, Amith Ananthram +5
With a combination of quantitative experiments, human judgments, and qualitative analyses, we evaluate the quantity and quality of African American Language (AAL) representation in…
Enhancing Multimodal Affective Analysis with Learned Live Comment Features
Zhaoyuan Deng, Amith Ananthram, Kathleen McKeown
Live comments, also known as Danmaku, are user-generated messages that are synchronized with video content. These comments overlay directly onto streaming videos, capturing viewer…
See It from My Perspective: How Language Affects Cultural Bias in Image Understanding
Amith Ananthram, Elias Stengel-Eskin, Mohit Bansal +1
Vision-language models (VLMs) can respond to queries about images in many languages. However, beyond language, culture affects how we see things. For example, individuals from West…
Social Orientation: A New Feature for Dialogue Analysis
Todd Morrill, Zhaoyuan Deng, Yanda Chen +3
There are many settings where it is useful to predict and explain the success or failure of a dialogue. Circumplex theory from psychology models the social orientations (e.g., Warm…
Check-COVID: Fact-Checking COVID-19 News Claims with Scientific Evidence
Gengyu Wang, Kate Harwood, Lawrence Chillrud +3
We present a new fact-checking benchmark, Check-COVID, that requires systems to verify claims about COVID-19 from news using evidence from scientific articles. This approach to fac…
Seeded Hierarchical Clustering for Expert-Crafted Taxonomies
Anish Saha, Amith Ananthram, Emily Allaway +2
Practitioners from many disciplines (e.g., political science) use expert-crafted taxonomies to make sense of large, unlabeled corpora. In this work, we study Seeded Hierarchical Cl…
Event Guided Denoising for Multilingual Relation Learning
Amith Ananthram, Emily Allaway, Kathleen McKeown
General purpose relation extraction has recently seen considerable gains in part due to a massively data-intensive distant supervision technique from Soares et al. (2019) that prod…
Multi-Modal Emotion Detection with Transfer Learning
Amith Ananthram, Kailash Karthik Saravanakumar, Jessica Huynh +1
Automated emotion detection in speech is a challenging task due to the complex interdependence between words and the manner in which they are spoken. It is made more difficult by t…