Samuel Stevens

A continental-scale dataset of ground beetles with high-resolution images and validated morphological trait measurements

S M Rayeed, Mridul Khurana, Alyson East, Isadora E. Fluck et autres

Abstract Despite the ecological significance of invertebrates, global trait databases remain heavily biased toward vertebrates and plants, limiting comprehensive ecological analyses of high-diversity groups like ground beetles. Ground beetles ( Coleoptera: Carabidae ) serve as critical bioindicators of ecosystem health, providing valuable …

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From collection trays to AI-ready data: An operational framework for automated batch entomological specimen processing

Alyson East, S M Rayeed, Elizabeth G. Campolongo, Nathan Cain et autres

Natural history collections house over three billion specimens critical to biodiversity research, yet fewer than 2% of North American arthropod specimens have been imaged, creating a bottleneck for trait-based analyses at broad temporal and spatial scales. Batch photography of multiple specimens improves …

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saev: Sparse Autoencoders for Vision Transformers

Samuel Stevens

saev is a package for training sparse autoencoders (SAEs) on vision transformers (ViTs) in PyTorch.

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saev: Sparse Autoencoders for Vision Transformers

Samuel Stevens

saev is a package for training sparse autoencoders (SAEs) on vision transformers (ViTs) in PyTorch.

us (code pays fourni par la source)

A continental-scale dataset of ground beetles with high-resolution images and validated morphological trait measurements

S M Rayeed, Mridul Khurana, Alyson East, Isadora E. Fluck et autres

Despite the ecological significance of invertebrates, global trait databases remain heavily biased toward vertebrates and plants, limiting comprehensive ecological analyses of high-diversity groups like ground beetles. Ground beetles (Coleoptera: Carabidae) serve as critical bioindicators of ecosystem health, providing valuable insights into biodiversity …

Optimizing image capture for computer vision‐powered taxonomic identification and trait recognition of biodiversity specimens

Alyson East, Elizabeth Campolongo, Luke Meyers, S M Rayeed et autres

Abstract Biological collections house millions of specimens with digital images increasingly available through open‐access platforms. However, most imaging protocols were developed for human interpretation without considering automated analysis requirements. As computer vision applications revolutionize taxonomic identification and trait extraction, a critical gap …

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

Yue Xiang, Yuansheng Ni, Tianyu Zheng, Kai Zhang et autres

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 text-books, covering six core disciplines: Art & Design, …

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

Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng et autres

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 disciplines: Art & Design, …

Roll Up Your Sleeves: Working with a Collaborative and Engaging Task-Oriented Dialogue System

Lingbo Mo, Shijie Chen, Ziru Chen, Xiang Deng et autres

We introduce TacoBot, a user-centered task-oriented digital assistant designed to guide users through complex real-world tasks with multiple steps. Covering a wide range of cooking and how-to tasks, we aim to deliver a collaborative and engaging dialogue experience. Equipped with language understanding, …

Mind2Web: Towards a Generalist Agent for the Web

Xiang Deng, 裕二 池谷, Boyuan Zheng, Shijie Chen et autres

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 …

Memorization for Good: Encryption with Autoregressive Language Models

Samuel Stevens, Yu Su

Over-parameterized neural language models (LMs) can memorize and recite long sequences of training data. While such memorization is normally associated with undesired properties such as overfitting and information leaking, our work casts memorization as an unexplored capability of LMs. We propose the …

Roll Up Your Sleeves: Working with a Collaborative and Engaging Task-Oriented Dialogue System

Lingbo Mo, Shijie Chen, Ziru Chen, Xiang Deng et autres

Lingbo Mo, Shijie Chen, Ziru Chen, Xiang Deng, Ashley Lewis, Sunit Singh, Samuel Stevens, Chang-You Tai, Zhen Wang, Xiang Yue, Tianshu Zhang, Yu Su, Huan Sun. Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue. 2023.

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