✨Rethinking LLM-as-a-Judge: Representation-as-a-Judge with Small Language Models via Semantic Capacity Asymmetry
📝 Summary:
Small language models can effectively evaluate outputs by leveraging internal representations rather than generating responses, enabling a more efficient and interpretable evaluation approach through ...
🔹 Publication Date: Published on Jan 30
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.22588
• PDF: https://arxiv.org/pdf/2601.22588
• Github: https://github.com/zhuochunli/Representation-as-a-judge
==================================
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📝 Summary:
Small language models can effectively evaluate outputs by leveraging internal representations rather than generating responses, enabling a more efficient and interpretable evaluation approach through ...
🔹 Publication Date: Published on Jan 30
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.22588
• PDF: https://arxiv.org/pdf/2601.22588
• Github: https://github.com/zhuochunli/Representation-as-a-judge
==================================
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✨WildGraphBench: Benchmarking GraphRAG with Wild-Source Corpora
📝 Summary:
WildGraphBench evaluates GraphRAG performance in realistic scenarios using Wikipedia's structured content to assess multi-fact aggregation and summarization capabilities across diverse document types....
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02053
• PDF: https://arxiv.org/pdf/2602.02053
==================================
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📝 Summary:
WildGraphBench evaluates GraphRAG performance in realistic scenarios using Wikipedia's structured content to assess multi-fact aggregation and summarization capabilities across diverse document types....
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02053
• PDF: https://arxiv.org/pdf/2602.02053
==================================
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✨RLAnything: Forge Environment, Policy, and Reward Model in Completely Dynamic RL System
📝 Summary:
RLAnything enhances reinforcement learning for LLMs and agents through dynamic model optimization and closed-loop feedback mechanisms that improve policy and reward model training. AI-generated summar...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02488
• PDF: https://arxiv.org/pdf/2602.02488
• Project Page: https://huggingface.co/collections/Gen-Verse/open-agentrl
• Github: https://github.com/Gen-Verse/Open-AgentRL
🔹 Models citing this paper:
• https://huggingface.co/Gen-Verse/RLAnything-Alf-7B
• https://huggingface.co/Gen-Verse/RLAnything-Alf-Reward-14B
• https://huggingface.co/Gen-Verse/RLAnything-OS-Reward-8B
==================================
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📝 Summary:
RLAnything enhances reinforcement learning for LLMs and agents through dynamic model optimization and closed-loop feedback mechanisms that improve policy and reward model training. AI-generated summar...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02488
• PDF: https://arxiv.org/pdf/2602.02488
• Project Page: https://huggingface.co/collections/Gen-Verse/open-agentrl
• Github: https://github.com/Gen-Verse/Open-AgentRL
🔹 Models citing this paper:
• https://huggingface.co/Gen-Verse/RLAnything-Alf-7B
• https://huggingface.co/Gen-Verse/RLAnything-Alf-Reward-14B
• https://huggingface.co/Gen-Verse/RLAnything-OS-Reward-8B
==================================
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✨Wiki Live Challenge: Challenging Deep Research Agents with Expert-Level Wikipedia Articles
📝 Summary:
Deep Research Agents demonstrate capabilities in autonomous information retrieval but show significant gaps when evaluated against expert-level Wikipedia articles using a new live benchmark and compre...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01590
• PDF: https://arxiv.org/pdf/2602.01590
==================================
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📝 Summary:
Deep Research Agents demonstrate capabilities in autonomous information retrieval but show significant gaps when evaluated against expert-level Wikipedia articles using a new live benchmark and compre...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01590
• PDF: https://arxiv.org/pdf/2602.01590
==================================
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✨Closing the Loop: Universal Repository Representation with RPG-Encoder
📝 Summary:
RPG-Encoder framework transforms repository comprehension and generation into a unified cycle by encoding code into high-fidelity Repository Planning Graph representations that improve understanding a...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02084
• PDF: https://arxiv.org/pdf/2602.02084
• Project Page: https://ayanami2003.github.io/RPG-Encoder/
• Github: https://github.com/microsoft/RPG-ZeroRepo
==================================
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📝 Summary:
RPG-Encoder framework transforms repository comprehension and generation into a unified cycle by encoding code into high-fidelity Repository Planning Graph representations that improve understanding a...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02084
• PDF: https://arxiv.org/pdf/2602.02084
• Project Page: https://ayanami2003.github.io/RPG-Encoder/
• Github: https://github.com/microsoft/RPG-ZeroRepo
==================================
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✨Toward Cognitive Supersensing in Multimodal Large Language Model
📝 Summary:
MLLMs equipped with Cognitive Supersensing and Latent Visual Imagery Prediction demonstrate enhanced cognitive reasoning capabilities through integrated visual and textual reasoning pathways. AI-gener...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01541
• PDF: https://arxiv.org/pdf/2602.01541
• Project Page: https://pediamedai.com/Cognition-MLLM/cogsense/
• Github: https://github.com/PediaMedAI/Cognition-MLLM
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📝 Summary:
MLLMs equipped with Cognitive Supersensing and Latent Visual Imagery Prediction demonstrate enhanced cognitive reasoning capabilities through integrated visual and textual reasoning pathways. AI-gener...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01541
• PDF: https://arxiv.org/pdf/2602.01541
• Project Page: https://pediamedai.com/Cognition-MLLM/cogsense/
• Github: https://github.com/PediaMedAI/Cognition-MLLM
==================================
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✨Making Avatars Interact: Towards Text-Driven Human-Object Interaction for Controllable Talking Avatars
📝 Summary:
A dual-stream framework called InteractAvatar is presented for generating talking avatars that can interact with objects in their environment, addressing challenges in grounded human-object interactio...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01538
• PDF: https://arxiv.org/pdf/2602.01538
• Github: https://github.com/angzong/InteractAvatar
==================================
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📝 Summary:
A dual-stream framework called InteractAvatar is presented for generating talking avatars that can interact with objects in their environment, addressing challenges in grounded human-object interactio...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01538
• PDF: https://arxiv.org/pdf/2602.01538
• Github: https://github.com/angzong/InteractAvatar
==================================
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✨Beyond Pixels: Visual Metaphor Transfer via Schema-Driven Agentic Reasoning
📝 Summary:
Visual metaphor transfer enables creative AI systems to decompose abstract conceptual relationships from reference images and reapply them to new subjects through a multi-agent framework grounded in c...
🔹 Publication Date: Published on Feb 1
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01335
• PDF: https://arxiv.org/pdf/2602.01335
==================================
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📝 Summary:
Visual metaphor transfer enables creative AI systems to decompose abstract conceptual relationships from reference images and reapply them to new subjects through a multi-agent framework grounded in c...
🔹 Publication Date: Published on Feb 1
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01335
• PDF: https://arxiv.org/pdf/2602.01335
==================================
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✨Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models
📝 Summary:
Vision-DeepResearch benchmark addresses limitations in evaluating visual-textual search capabilities of multimodal models by introducing realistic evaluation conditions and improving visual retrieval ...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02185
• PDF: https://arxiv.org/pdf/2602.02185
• Project Page: https://osilly.github.io/Vision-DeepResearch/
==================================
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📝 Summary:
Vision-DeepResearch benchmark addresses limitations in evaluating visual-textual search capabilities of multimodal models by introducing realistic evaluation conditions and improving visual retrieval ...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02185
• PDF: https://arxiv.org/pdf/2602.02185
• Project Page: https://osilly.github.io/Vision-DeepResearch/
==================================
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✨Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models
📝 Summary:
Vision-DeepResearch introduces a multimodal deep-research paradigm enabling multi-turn, multi-entity, and multi-scale visual and textual search with deep-research capabilities integrated through cold-...
🔹 Publication Date: Published on Jan 29
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.22060
• PDF: https://arxiv.org/pdf/2601.22060
• Project Page: https://osilly.github.io/Vision-DeepResearch/
• Github: https://github.com/Osilly/Vision-DeepResearch
==================================
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📝 Summary:
Vision-DeepResearch introduces a multimodal deep-research paradigm enabling multi-turn, multi-entity, and multi-scale visual and textual search with deep-research capabilities integrated through cold-...
🔹 Publication Date: Published on Jan 29
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.22060
• PDF: https://arxiv.org/pdf/2601.22060
• Project Page: https://osilly.github.io/Vision-DeepResearch/
• Github: https://github.com/Osilly/Vision-DeepResearch
==================================
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✨Kimi K2.5: Visual Agentic Intelligence
📝 Summary:
Kimi K2.5 is an open-source multimodal agentic model that enhances text and vision processing through joint optimization techniques and introduces Agent Swarm for parallel task execution. AI-generated...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02276
• PDF: https://arxiv.org/pdf/2602.02276
• Project Page: https://huggingface.co/moonshotai/Kimi-K2.5
==================================
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📝 Summary:
Kimi K2.5 is an open-source multimodal agentic model that enhances text and vision processing through joint optimization techniques and introduces Agent Swarm for parallel task execution. AI-generated...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02276
• PDF: https://arxiv.org/pdf/2602.02276
• Project Page: https://huggingface.co/moonshotai/Kimi-K2.5
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✨Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation
📝 Summary:
A novel Causal Forcing method addresses the architectural gap in distilling bidirectional video diffusion models into autoregressive models by using AR teachers for ODE initialization, significantly i...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02214
• PDF: https://arxiv.org/pdf/2602.02214
• Project Page: https://thu-ml.github.io/CausalForcing.github.io/
• Github: https://thu-ml.github.io/CausalForcing.github.io/
🔹 Models citing this paper:
• https://huggingface.co/zhuhz22/Causal-Forcing
==================================
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📝 Summary:
A novel Causal Forcing method addresses the architectural gap in distilling bidirectional video diffusion models into autoregressive models by using AR teachers for ODE initialization, significantly i...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02214
• PDF: https://arxiv.org/pdf/2602.02214
• Project Page: https://thu-ml.github.io/CausalForcing.github.io/
• Github: https://thu-ml.github.io/CausalForcing.github.io/
🔹 Models citing this paper:
• https://huggingface.co/zhuhz22/Causal-Forcing
==================================
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✨Mind-Brush: Integrating Agentic Cognitive Search and Reasoning into Image Generation
📝 Summary:
Mind-Brush presents a unified agentic framework for text-to-image generation that dynamically retrieves multimodal evidence and employs reasoning tools to improve understanding of implicit user intent...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01756
• PDF: https://arxiv.org/pdf/2602.01756
• Github: https://github.com/PicoTrex/Mind-Brush
==================================
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📝 Summary:
Mind-Brush presents a unified agentic framework for text-to-image generation that dynamically retrieves multimodal evidence and employs reasoning tools to improve understanding of implicit user intent...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01756
• PDF: https://arxiv.org/pdf/2602.01756
• Github: https://github.com/PicoTrex/Mind-Brush
==================================
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✨Interacted Planes Reveal 3D Line Mapping
📝 Summary:
LiP-Map presents a line-plane joint optimization framework that explicitly models learnable line and planar primitives for accurate 3D line mapping in man-made environments. AI-generated summary 3D li...
🔹 Publication Date: Published on Feb 1
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01296
• PDF: https://arxiv.org/pdf/2602.01296
• Github: https://github.com/calmke/LiPMAP
==================================
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📝 Summary:
LiP-Map presents a line-plane joint optimization framework that explicitly models learnable line and planar primitives for accurate 3D line mapping in man-made environments. AI-generated summary 3D li...
🔹 Publication Date: Published on Feb 1
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01296
• PDF: https://arxiv.org/pdf/2602.01296
• Github: https://github.com/calmke/LiPMAP
==================================
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✨UniReason 1.0: A Unified Reasoning Framework for World Knowledge Aligned Image Generation and Editing
📝 Summary:
UniReason integrates text-to-image generation and image editing through a dual reasoning paradigm that enhances planning with world knowledge and uses editing for visual refinement, achieving superior...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02437
• PDF: https://arxiv.org/pdf/2602.02437
🔹 Models citing this paper:
• https://huggingface.co/Alex11556666/UniReason
==================================
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📝 Summary:
UniReason integrates text-to-image generation and image editing through a dual reasoning paradigm that enhances planning with world knowledge and uses editing for visual refinement, achieving superior...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02437
• PDF: https://arxiv.org/pdf/2602.02437
🔹 Models citing this paper:
• https://huggingface.co/Alex11556666/UniReason
==================================
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✨Prism: Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion Language Models
📝 Summary:
A new test-time scaling framework called Prism is introduced for discrete diffusion language models that improves reasoning performance through hierarchical trajectory search, local branching with par...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01842
• PDF: https://arxiv.org/pdf/2602.01842
• Github: https://github.com/viiika/Prism
==================================
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📝 Summary:
A new test-time scaling framework called Prism is introduced for discrete diffusion language models that improves reasoning performance through hierarchical trajectory search, local branching with par...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01842
• PDF: https://arxiv.org/pdf/2602.01842
• Github: https://github.com/viiika/Prism
==================================
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✨CoDiQ: Test-Time Scaling for Controllable Difficult Question Generation
📝 Summary:
A novel framework called CoDiQ enables controllable difficulty generation for competition-level questions through test-time scaling, resulting in a corpus that significantly improves large reasoning m...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01660
• PDF: https://arxiv.org/pdf/2602.01660
🔹 Models citing this paper:
• https://huggingface.co/AleXGroup/CoDiQ-Gen-8B
✨ Datasets citing this paper:
• https://huggingface.co/datasets/AleXGroup/CoDiQ-Corpus
==================================
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📝 Summary:
A novel framework called CoDiQ enables controllable difficulty generation for competition-level questions through test-time scaling, resulting in a corpus that significantly improves large reasoning m...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01660
• PDF: https://arxiv.org/pdf/2602.01660
🔹 Models citing this paper:
• https://huggingface.co/AleXGroup/CoDiQ-Gen-8B
✨ Datasets citing this paper:
• https://huggingface.co/datasets/AleXGroup/CoDiQ-Corpus
==================================
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✨On the Relationship Between Representation Geometry and Generalization in Deep Neural Networks
📝 Summary:
Effective dimension, an unsupervised geometric metric, strongly predicts neural network performance across different architectures and domains, showing bidirectional causality between representation g...
🔹 Publication Date: Published on Jan 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.00130
• PDF: https://arxiv.org/pdf/2602.00130
==================================
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📝 Summary:
Effective dimension, an unsupervised geometric metric, strongly predicts neural network performance across different architectures and domains, showing bidirectional causality between representation g...
🔹 Publication Date: Published on Jan 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.00130
• PDF: https://arxiv.org/pdf/2602.00130
==================================
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✨RE-TRAC: REcursive TRAjectory Compression for Deep Search Agents
📝 Summary:
Re-TRAC is an agentic framework that enhances LLM-based research agents by enabling cross-trajectory exploration and iterative reflection through structured state representations, leading to more effi...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02486
• PDF: https://arxiv.org/pdf/2602.02486
==================================
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📝 Summary:
Re-TRAC is an agentic framework that enhances LLM-based research agents by enabling cross-trajectory exploration and iterative reflection through structured state representations, leading to more effi...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02486
• PDF: https://arxiv.org/pdf/2602.02486
==================================
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❤1
✨SEA-Guard: Culturally Grounded Multilingual Safeguard for Southeast Asia
📝 Summary:
Researchers developed a novel agentic data-generation framework to create culturally grounded safety datasets for Southeast Asia, resulting in multilingual safeguard models that outperform existing ap...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01618
• PDF: https://arxiv.org/pdf/2602.01618
==================================
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📝 Summary:
Researchers developed a novel agentic data-generation framework to create culturally grounded safety datasets for Southeast Asia, resulting in multilingual safeguard models that outperform existing ap...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.01618
• PDF: https://arxiv.org/pdf/2602.01618
==================================
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✨Structured 3D Latents for Scalable and Versatile 3D Generation
📝 Summary:
A 3D generation method using a unified SLAT representation and rectified flow transformers achieves high-quality results across different formats and conditions. AI-generated summary We introduce a no...
🔹 Publication Date: Published on Dec 2, 2024
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2412.01506
• PDF: https://arxiv.org/pdf/2412.01506
• Github: https://github.com/Microsoft/TRELLIS
🔹 Models citing this paper:
• https://huggingface.co/microsoft/TRELLIS-image-large
• https://huggingface.co/microsoft/TRELLIS-text-xlarge
• https://huggingface.co/microsoft/TRELLIS-text-base
✨ Datasets citing this paper:
• https://huggingface.co/datasets/JeffreyXiang/TRELLIS-500K
• https://huggingface.co/datasets/argojuni0506/TRELLIS-3D
• https://huggingface.co/datasets/gqk/TRELLIS-500K-fork
✨ Spaces citing this paper:
• https://huggingface.co/spaces/trellis-community/TRELLIS
• https://huggingface.co/spaces/dkatz2391/Cavargas-TRELLIS-Multiple3D
• https://huggingface.co/spaces/microsoft/TRELLIS
==================================
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📝 Summary:
A 3D generation method using a unified SLAT representation and rectified flow transformers achieves high-quality results across different formats and conditions. AI-generated summary We introduce a no...
🔹 Publication Date: Published on Dec 2, 2024
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2412.01506
• PDF: https://arxiv.org/pdf/2412.01506
• Github: https://github.com/Microsoft/TRELLIS
🔹 Models citing this paper:
• https://huggingface.co/microsoft/TRELLIS-image-large
• https://huggingface.co/microsoft/TRELLIS-text-xlarge
• https://huggingface.co/microsoft/TRELLIS-text-base
✨ Datasets citing this paper:
• https://huggingface.co/datasets/JeffreyXiang/TRELLIS-500K
• https://huggingface.co/datasets/argojuni0506/TRELLIS-3D
• https://huggingface.co/datasets/gqk/TRELLIS-500K-fork
✨ Spaces citing this paper:
• https://huggingface.co/spaces/trellis-community/TRELLIS
• https://huggingface.co/spaces/dkatz2391/Cavargas-TRELLIS-Multiple3D
• https://huggingface.co/spaces/microsoft/TRELLIS
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arXiv.org
Structured 3D Latents for Scalable and Versatile 3D Generation
We introduce a novel 3D generation method for versatile and high-quality 3D asset creation. The cornerstone is a unified Structured LATent (SLAT) representation which allows decoding to different...