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Samuel Stevens

8 accepted papers

2026

Automatic Image-Level Morphological Trait Annotation for Organismal Images

ICLR 2026poster

Morphological traits are physical characteristics of biological organisms that provide vital clues on how organisms interact with their environment. Yet extracting these traits remains a slow, expert-driven process, limiting their use in large-scale ecological studies. A major bottleneck is the abse…

Cited by 0SourcecodeScholar
2026

BioCAP: Exploiting Synthetic Captions Beyond Labels in Biological Foundation Models

ICLR 2026poster

This work investigates descriptive captions as an additional source of supervision for biological multimodal foundation models. Images and captions can be viewed as complementary samples from the latent morphospace of a species, each capturing certain biological traits. Incorporating captions during…

Cited by 0SourcecodeScholar
2025

BioCLIP 2: Emergent Properties from Scaling Hierarchical Contrastive Learning

NeurIPS 2025spotlight

Foundation models trained at scale exhibit remarkable emergent behaviors, learning new capabilities beyond their initial training objectives. We find such emergent behaviors in biological vision models via large-scale contrastive vision-language training. To achieve this, we first curate TreeOfLife-…

Cited by 0SourcecodeScholar
2024

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

ICLR 2024poster

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 class information to make predictions, we investigate a proactive approach, asking each class to search for itself in an im…

2024

BioCLIP: A Vision Foundation Model for the Tree of Life

CVPR 2024poster

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 of computational methods and tools particularly computer vision for extracting biologically relevant information from imag…

2024

MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

CVPR 2024poster

We introduce MMMU: a new benchmark designed to evaluate multimodal models on massive multi-discipline tasks demanding college-level subject knowledge and deliberate reasoning. MMMU includes 11.5K meticulously collected multimodal questions from college exams quizzes and textbooks covering six core d…

2023

Mind2Web: Towards a Generalist Agent for the Web

NeurIPS 2023spotlight

We introduce Mind2Web, the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus…

2022

arXivEdits: Understanding the Human Revision Process in Scientific Writing

EMNLP 2022main

Scientific publications are the primary means to communicate research discoveries, where the writing quality is of crucial importance. However, prior work studying the human editing process in this domain mainly focused on the abstract or introduction sections, resulting in an incomplete picture. In…