activity
20232026
most citedBioCLIP: A Vision Foundation Model for the Tree of Life

10 citations · 17 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

TaxaAdapter: Vision Taxonomy Models are Key to Fine-grained Image Generation over the Tree of Life

Mridul Khurana, Amin Karimi Monsefi, Justin Lee +9

Accurately generating images across the Tree of Life is difficult: there are over 10M distinct species on Earth, many of which differ only by subtle visual traits. Despite the rema…

cs.CV2025

Finer-Personalization Rank: Fine-Grained Retrieval Examines Identity Preservation for Personalized Generation

Connor Kilrain, David Carlyn, Julia Chae +3

The rise of personalized generative models raises a central question: how should we evaluate identity preservation? Given a reference image (e.g., one's pet), we expect the generat…

cs.LG2025

Building Machine Learning Challenges for Anomaly Detection in Science

Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova +148

Scientific discoveries are often made by finding a pattern or object that was not predicted by the known rules of science. Oftentimes, these anomalous events or objects that do not…

cs.CV2025★ 1 cited

Finer-CAM: Spotting the Difference Reveals Finer Details for Visual Explanation

Ziheng Zhang, Jianyang Gu, Arpita Chowdhury +5

Class activation map (CAM) has been widely used to highlight image regions that contribute to class predictions. Despite its simplicity and computational efficiency, CAM often stru…

cs.CV2023★ 10 cited

BioCLIP: A Vision Foundation Model for the Tree of Life

Samuel Stevens, Jiaman Wu, Matthew J Thompson +9

Images of the natural world, collected by a variety of cameras, from drones to individual phones, are increasingly abundant sources of biological information. There is an explosion…

cs.CV2023★ 5 cited

A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis

Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong +11

We present a novel usage of Transformers to make image classification interpretable. Unlike mainstream classifiers that wait until the last fully connected layer to incorporate cla…

cs.LG2023★ 1 cited

Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks

Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran +15

Discovering evolutionary traits that are heritable across species on the tree of life (also referred to as a phylogenetic tree) is of great interest to biologists to understand how…

cs.CV2023

Learning Fractals by Gradient Descent

Cheng-Hao Tu, Hong-You Chen, David Carlyn +1

Fractals are geometric shapes that can display complex and self-similar patterns found in nature (e.g., clouds and plants). Recent works in visual recognition have leveraged this p…