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PokéChamp: an Expert-level Minimax Language Agent

Mar 7, 2025 | huggingface.co | Seth Karten |Andy Nguyen |Andy Nguyễn |Chi Jin

Papers Published on Mar 6 · Submitted by akhaliq on Mar 7 Abstract We introduce Pok\'eChamp, a minimax agent powered by Large Language Models(LLMs) for Pok\'emon battles. Built on a general framework for two-playercompetitive games, Pok\'eChamp leverages the generalist capabilities of LLMs toenhance minimax tree search.
Paper page - UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface

Mar 5, 2025 | huggingface.co | Hao Tang |Chenwei Xie |Haiyang Wang |Xiaoyi Bao

Papers Published on Mar 3 · Submitted by kanashi6 on Mar 5 Abstract Generalist models have achieved remarkable success in both language andvision-language tasks, showcasing the potential of unified modeling.
Paper page - ChartCitor: Multi-Agent Framework for Fine-Grained Chart Visual Attribution

Feb 7, 2025 | huggingface.co | Kanika Goswami |Puneet Mathur |Ryan Rossi |Franck Dernoncourt

Papers Published on Feb 3 · Submitted by Franck-Dernoncourt on Feb 7 Abstract Large Language Models (LLMs) can perform chart question-answering tasks butoften generate unverified hallucinated responses.
Paper page - Exploring the sustainable scaling of AI dilemma: A projective study of corporations' AI environmental impacts

Jan 24, 2025 | huggingface.co

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In-situ graph reasoning and knowledge expansion using Graph-PReFLexOR

Jan 15, 2025 | huggingface.co | Markus J. Buehler

In Situ Graph Reasoning and Knowledge Expansion Using Graph-PReFLexOR: The work explains how to grow knowledge gardens, how to integrate symbolic and connectionist frameworks, and explains how 'thin places' inspired by Celtic mythology are related to bioluminescence. Graph-PReFLexOR integrates graph-based reasoning, symbolic abstraction, and recursive reflection.
Paper page - rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

Jan 9, 2025 | huggingface.co | Xinyu Guan |Li Zhang |Yifei Liu |Ning Shang

Papers Published on Jan 8 · Submitted by lynazhang on Jan 9 #1 Paper of the day Abstract We present rStar-Math to demonstrate that small language models (SLMs) canrival or even surpass the math reasoning capability of OpenAI o1, withoutdistillation from superior models.
Paper page - Dolphin: Closed-loop Open-ended Auto-research through Thinking, Practice, and Feedback

Jan 8, 2025 | huggingface.co | Jiakang Yuan |Xiangchao Yan |Botian Shi |Tao Chen

Papers Published on Jan 7 · Submitted by BoZhang on Jan 8 Abstract The scientific research paradigm is undergoing a profound transformationowing to the development of Artificial Intelligence (AI).
Faster Text Generation with Self-Speculative Decoding

Nov 20, 2024 | huggingface.co | AutoModel ForCausalLM

ariG23498 Aritra Roy Gosthipaty melhoushi Mostafa Elhoushi facebook pcuenq Pedro Cuenca reach-vb Vaibhav Srivastav Self-speculative decoding, proposed in LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding is a novel approach to text generation. It combines the strengths of speculative decoding with early exiting from a large language model (LLM). This method allows for efficient generation by using the same model's early layers for drafting tokens, and later layers for...
harpreetsahota/marvel-masterpieces · Datasets at Hugging Face

Nov 5, 2024 | huggingface.co | Harpreet Sahota

This is a FiftyOne dataset with 255 samples. Installation If you haven't already, install FiftyOne:pip install -U fiftyone Usage import fiftyone as fofrom fiftyone.utils.huggingface import load_from_hubdataset = load_from_hub("harpreetsahota/marvel-masterpieces")session = fo.launch_app(dataset) Dataset Details All images are scraped from the Marvel Fandom Database. This content is available under CC-BY-SA.
harpreetsahota/marvel-masterpieces-with-3dmesh · Datasets at Hugging Face

Nov 5, 2024 | huggingface.co | Harpreet Sahota

Search is not available for this dataset SQL Console