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New research from Meta FAIR — Meta Explore Theory-of-Mind: Program guided adversarial data generation for theory of mind reasoning. This work includes a new research paper, code & a dataset on Hugging Face. Details + eight more new releases from FAIR ➡️

AI at Meta

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38,568 次观看 • 1 年前 •via X (Twitter)

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Zoe Wang1 年前

Breakdown of the paper: The paper introduces ExploreToM, a framework for generating diverse and challenging data to evaluate and train large language models (LLMs) on theory of mind reasoning. Theory of mind is the ability to understand others' intentions, beliefs, and mental states, which is crucial for social intelligence. The ExploreToM-generated data is highly challenging for state-of-the-art LLMs, with accuracies as low as 0% and 9% for Llama-3.1-70B and GPT-4o, respectively. The authors found that LLMs struggle with basic state tracking, which is a prerequisite for theory of mind reasoning. They also showed that fine-tuning on ExploreToM data can significantly improve performance on existing theory of mind benchmarks. full paper:

Data & Analytics 的头像

Data & Analytics1 年前

@huggingface @AIatMeta, yo, that sounds like some cutting-edge stuff from Meta. Theory of mind in AI? That's deep! How do you think it’ll impact our interaction with tech?

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Electe1 年前

@huggingface @AIatMeta, exciting developments in theory-of-mind reasoning. 📚

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Wrapping up the year and coinciding with #NeurIPS2024, today at Meta FAIR we’re releasing a collection of nine new open source AI research artifacts across our work in developing agents, robustness & safety and new architectures. More in the video from Joelle Pineau. All of this work is part of FAIR’s continued work towards the goal of achieving advanced machine intelligence A few highlights from what we’re releasing today: • Meta Motivo: A first-of-its-kind behavioral foundation model that controls the movements of a virtual embodied humanoid agent to perform complex tasks. • Meta Video Seal: a state-of-the art comprehensive framework for neural video watermarking. • Meta Explore Theory-of-Mind: A program-guided adversarial data generation for theory of mind reasoning. • Meta Large Concept Models: A fundamentally different training paradigm for language modeling that decouples reasoning from language representation. And much more! We’re excited to share this work with the research community and look forward to seeing how it inspires new innovation across the field. Details and access to everything released by FAIR today ➡️

Wrapping up the year and coinciding with #NeurIPS2024, today at Meta FAIR we’re releasing a collection of nine new open source AI research artifacts across our work in developing agents, robustness & safety and new architectures. More in the video from Joelle Pineau. All of this work is part of FAIR’s continued work towards the goal of achieving advanced machine intelligence A few highlights from what we’re releasing today: • Meta Motivo: A first-of-its-kind behavioral foundation model that controls the movements of a virtual embodied humanoid agent to perform complex tasks. • Meta Video Seal: a state-of-the art comprehensive framework for neural video watermarking. • Meta Explore Theory-of-Mind: A program-guided adversarial data generation for theory of mind reasoning. • Meta Large Concept Models: A fundamentally different training paradigm for language modeling that decouples reasoning from language representation. And much more! We’re excited to share this work with the research community and look forward to seeing how it inspires new innovation across the field. Details and access to everything released by FAIR today ➡️

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156,008 次观看 • 1 年前

New research from Meta FAIR — Meta Memory Layers at Scale. This work takes memory layers beyond proof-of-concept, proving their utility at contemporary scale ➡️

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156,086 次观看 • 1 年前

We previously shared our research on Layer Skip, an end-to-end solution for accelerating LLMs from researchers at Meta FAIR. It achieves this by executing a subset of an LLM’s layers and utilizing subsequent layers for verification and correction. We’re now releasing inference code and fine-tuned checkpoints for this work. Model weights on Hugging Face ➡️ More details ➡️ We hope that releasing this work will open up new areas of experimentation and innovative new research in optimization and interpretability.

We previously shared our research on Layer Skip, an end-to-end solution for accelerating LLMs from researchers at Meta FAIR. It achieves this by executing a subset of an LLM’s layers and utilizing subsequent layers for verification and correction. We’re now releasing inference code and fine-tuned checkpoints for this work. Model weights on Hugging Face ➡️ More details ➡️ We hope that releasing this work will open up new areas of experimentation and innovative new research in optimization and interpretability.

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156,581 次观看 • 1 年前

A closer look at the evolution of the research from Meta FAIR that led to our latest open source work for human-robot collaboration. Details on Meta PARTNR ➡️

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41,228 次观看 • 1 年前

New from Meta FAIR: Code World Model (CWM), a 32B-parameter research model designed to explore how world models can transform code generation and reasoning about code. We believe in advancing research in world modeling and are sharing CWM under a research license to help empower the community to build upon our work. ➡️ Read the technical report: ➡️Download the open weights: ➡️Download the code:

New from Meta FAIR: Code World Model (CWM), a 32B-parameter research model designed to explore how world models can transform code generation and reasoning about code. We believe in advancing research in world modeling and are sharing CWM under a research license to help empower the community to build upon our work. ➡️ Read the technical report: ➡️Download the open weights: ➡️Download the code:

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313,297 次观看 • 9 个月前

New AI research from Meta – CoTracker3 Simpler and Better Point Tracking by Pseudo-Labelling Real Videos. More details ➡️ Demo on Hugging Face ➡️ Building on our previous work on CoTracker, this new model demonstrates impressive tracking results where points can be tracked for a long time even when they're occluded or leave the field of view. CoTracker3 achieves state-of-the-art, outperforming all recent point tracking approaches on standard benchmarks — often by a substantial margin. We've released the research paper, code and a demo on Hugging Face — along with models available under an A-NC license to support further research in this space.

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218,910 次观看 • 1 年前

New research from Meta FAIR: Large Concept Models (LCM) is a fundamentally different paradigm for language modeling that decouples reasoning from language representation, inspired by how humans can plan high-level thoughts to communicate.

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531,486 次观看 • 1 年前

📣 New research from GenAI at Meta, introducing Meta 3D Gen: A new system for end-to-end generation of 3D assets from text in <1min. Meta 3D Gen is a new combined AI system that can generate high-quality 3D assets, with both high-resolution textures and material maps end-to-end, producing results that are superior to existing solutions — at 3-10x the speed of existing work in this space. Details in the technical report ➡️

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408,708 次观看 • 2 年前

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54,410 次观看 • 2 年前

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74,531 次观看 • 1 年前

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150,222 次观看 • 1 年前

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129,055 次观看 • 1 年前

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52,379 次观看 • 1 年前

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453,148 次观看 • 1 年前

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450,358 次观看 • 2 年前

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49,054 次观看 • 3 年前

Project Aria is a research program helping Meta unlock new possibilities of how we connect with and experience the world through AR and AI. 📺Watch the full tutorial from #CVPR2022 to learn how Project Aria will advance machine perception and AI research:

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14,720 次观看 • 3 年前

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380,701 次观看 • 2 年前