5 citations · 10 across the 15 of their papers we have counts for
18 papers
Autonomous Scientific Discovery via Iterative Meta-Reflection
Bingchen Zhao, Sara Beery, Oisin Mac Aodha
Autonomous scientific discovery systems offer the potential to accelerate research by automating the process of hypothesis generation and validation. However, current systems opera…
Decoupling the Declarative from the Procedural in Vision-Language-Action Models
Nikolaos Tsagkas, Andreas Sochopoulos, Chris Xiaoxuan Lu +2
Deploying generalist robotic agents in the real world requires transferable skills. Specifically, a policy trained to clone a behavior from object-specific demonstrations must gene…
roto 2.0: The Robot Tactile Olympiad
Elle Miller, Jayaram Reddy, Ayush Deshmukh +4
Tactile-based reinforcement learning (RL) is currently hindered by fragmented research and a focus on over-saturated orientation tasks. We introduce v2 of the Robot Tactile Olympia…
APRES: An Agentic Paper Revision and Evaluation System
Bingchen Zhao, Jenny Zhang, Chenxi Whitehouse +8
Scientific discoveries must be communicated clearly to realize their full potential. Without effective communication, even the most groundbreaking findings risk being overlooked or…
MotionPhysics: Learnable Motion Distillation for Text-Guided Simulation
Miaowei Wang, Jakub Zadrożny, Oisin Mac Aodha +1
Accurately simulating existing 3D objects and a wide variety of materials often demands expert knowledge and time-consuming physical parameter tuning to achieve the desired dynamic…
CleverBirds: A Multiple-Choice Benchmark for Fine-grained Human Knowledge Tracing
Leonie Bossemeyer, Samuel Heinrich, Grant Van Horn +1
Mastering fine-grained visual recognition, essential in many expert domains, can require that specialists undergo years of dedicated training. Modeling the progression of such expe…
INQUIRE-Search: Interactive Discovery in Large-Scale Biodiversity Databases
Edward Vendrow, Julia Chae, Rupa Kurinchi-Vendhan +10
Many ecological questions center on complex phenomena, such as species interactions, behaviors, phenology, and responses to disturbance, that are inherently difficult to observe an…
Enhancing Tactile-based Reinforcement Learning for Robotic Control
Elle Miller, Trevor McInroe, David Abel +2
Achieving safe, reliable real-world robotic manipulation requires agents to evolve beyond vision and incorporate tactile sensing to overcome sensory deficits and reliance on ideali…
Sample-efficient Integration of New Modalities into Large Language Models
Osman Batur İnce, André F. T. Martins, Oisin Mac Aodha +1
Multimodal foundation models can process several modalities. However, since the space of possible modalities is large and evolving over time, training a model from scratch to encom…
The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements
Bingchen Zhao, Despoina Magka, Minqi Jiang +20
Rapid advancements in large language models (LLMs) have the potential to assist in scientific progress. A critical capability toward this endeavor is the ability to reproduce exist…
Interpretable Text-Guided Image Clustering via Iterative Search
Bingchen Zhao, Oisin Mac Aodha
Traditional clustering methods aim to group unlabeled data points based on their similarity to each other. However, clustering, in the absence of additional information, is an ill-…
MVSAnywhere: Zero-Shot Multi-View Stereo
Sergio Izquierdo, Mohamed Sayed, Michael Firman +6
Computing accurate depth from multiple views is a fundamental and longstanding challenge in computer vision. However, most existing approaches do not generalize well across differe…
Feedforward Few-shot Species Range Estimation
Christian Lange, Max Hamilton, Elijah Cole +6
Knowing where a particular species can or cannot be found on Earth is crucial for ecological research and conservation efforts. By mapping the spatial ranges of all species, we wou…
acoupi: An Open-Source Python Framework for Deploying Bioacoustic AI Models on Edge Devices
Aude Vuilliomenet, Santiago Martínez Balvanera, Oisin Mac Aodha +2
1. Passive acoustic monitoring (PAM) coupled with artificial intelligence (AI) is becoming an essential tool for biodiversity monitoring. Traditional PAM systems require manual dat…
WildSAT: Learning Satellite Image Representations from Wildlife Observations
Rangel Daroya, Elijah Cole, Oisin Mac Aodha +2
Species distributions encode valuable ecological and environmental information, yet their potential for guiding representation learning in remote sensing remains underexplored. We…
INQUIRE: A Natural World Text-to-Image Retrieval Benchmark
Edward Vendrow, Omiros Pantazis, Alexander Shepard +5
We introduce INQUIRE, a text-to-image retrieval benchmark designed to challenge multimodal vision-language models on expert-level queries. INQUIRE includes iNaturalist 2024 (iNat24…
Combining Observational Data and Language for Species Range Estimation
Max Hamilton, Christian Lange, Elijah Cole +5
Species range maps (SRMs) are essential tools for research and policy-making in ecology, conservation, and environmental management. However, traditional SRMs rely on the availabil…
Generating Binary Species Range Maps
Filip Dorm, Christian Lange, Scott Loarie +1
Accurately predicting the geographic ranges of species is crucial for assisting conservation efforts. Traditionally, range maps were manually created by experts. However, species d…