✨SwiftVLA: Unlocking Spatiotemporal Dynamics for Lightweight VLA Models at Minimal Overhead
📝 Summary:
SwiftVLA enhances compact VLA models with efficient 4D understanding. It uses a 4D geometry transformer, Fusion Tokens, and a mask-and-reconstruct strategy. This rivals larger models while drastically improving speed and memory efficiency.
🔹 Publication Date: Published on Nov 30
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.00903
• PDF: https://arxiv.org/pdf/2512.00903
• Project Page: https://swiftvla.github.io/
• Github: https://swiftvla.github.io/
==================================
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#SwiftVLA #VLAModels #SpatiotemporalAI #EfficientAI #Transformers
📝 Summary:
SwiftVLA enhances compact VLA models with efficient 4D understanding. It uses a 4D geometry transformer, Fusion Tokens, and a mask-and-reconstruct strategy. This rivals larger models while drastically improving speed and memory efficiency.
🔹 Publication Date: Published on Nov 30
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.00903
• PDF: https://arxiv.org/pdf/2512.00903
• Project Page: https://swiftvla.github.io/
• Github: https://swiftvla.github.io/
==================================
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#SwiftVLA #VLAModels #SpatiotemporalAI #EfficientAI #Transformers
✨Mixture of Horizons in Action Chunking
📝 Summary:
VLA models struggle with a fixed action chunk horizon. The Mixture of Horizons MoH strategy combines different horizons for both global foresight and fine-grained precision. This improves robotic performance, generalizability, and throughput, achieving new state-of-the-art.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.19433
• PDF: https://arxiv.org/pdf/2511.19433
• Project Page: https://timsty1.github.io/moh/
• Github: https://github.com/Timsty1/MixtureOfHorizons/tree/main
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#Robotics #AI #MachineLearning #DeepLearning #ReinforcementLearning
📝 Summary:
VLA models struggle with a fixed action chunk horizon. The Mixture of Horizons MoH strategy combines different horizons for both global foresight and fine-grained precision. This improves robotic performance, generalizability, and throughput, achieving new state-of-the-art.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.19433
• PDF: https://arxiv.org/pdf/2511.19433
• Project Page: https://timsty1.github.io/moh/
• Github: https://github.com/Timsty1/MixtureOfHorizons/tree/main
==================================
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#Robotics #AI #MachineLearning #DeepLearning #ReinforcementLearning
✨WorldMM: Dynamic Multimodal Memory Agent for Long Video Reasoning
📝 Summary:
WorldMM is a novel multimodal memory agent for long video reasoning. It uses episodic, semantic, and visual memories with adaptive retrieval across multiple temporal scales, significantly outperforming prior methods on long video question-answering benchmarks.
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02425
• PDF: https://arxiv.org/pdf/2512.02425
• Project Page: https://worldmm.github.io
• Github: https://github.com/wgcyeo/WorldMM
==================================
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#MultimodalAI #VideoReasoning #MemoryNetworks #DeepLearning #AI
📝 Summary:
WorldMM is a novel multimodal memory agent for long video reasoning. It uses episodic, semantic, and visual memories with adaptive retrieval across multiple temporal scales, significantly outperforming prior methods on long video question-answering benchmarks.
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02425
• PDF: https://arxiv.org/pdf/2512.02425
• Project Page: https://worldmm.github.io
• Github: https://github.com/wgcyeo/WorldMM
==================================
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#MultimodalAI #VideoReasoning #MemoryNetworks #DeepLearning #AI
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✨BlockVid: Block Diffusion for High-Quality and Consistent Minute-Long Video Generation
📝 Summary:
BlockVid introduces a block diffusion framework for high-quality, coherent minute-long video generation. It overcomes error accumulation via a semantic-aware sparse KV cache, Block Forcing training, and dedicated noise scheduling. BlockVid outperforms existing methods and proposes LV-Bench, a new...
🔹 Publication Date: Published on Nov 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.22973
• PDF: https://arxiv.org/pdf/2511.22973
• Project Page: https://ziplab.co/BlockVid/
• Github: https://github.com/alibaba-damo-academy/Inferix/
==================================
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#VideoGeneration #DiffusionModels #GenerativeAI #DeepLearning #ComputerVision
📝 Summary:
BlockVid introduces a block diffusion framework for high-quality, coherent minute-long video generation. It overcomes error accumulation via a semantic-aware sparse KV cache, Block Forcing training, and dedicated noise scheduling. BlockVid outperforms existing methods and proposes LV-Bench, a new...
🔹 Publication Date: Published on Nov 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.22973
• PDF: https://arxiv.org/pdf/2511.22973
• Project Page: https://ziplab.co/BlockVid/
• Github: https://github.com/alibaba-damo-academy/Inferix/
==================================
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#VideoGeneration #DiffusionModels #GenerativeAI #DeepLearning #ComputerVision
✨Click2Graph: Interactive Panoptic Video Scene Graphs from a Single Click
📝 Summary:
Click2Graph is an interactive framework for Panoptic Video Scene Graph Generation. It uses a single user click to segment, track, discover interactions, and predict triplets for temporally consistent scene graphs. This enables user-guided, controllable video scene understanding.
🔹 Publication Date: Published on Nov 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.15948
• PDF: https://arxiv.org/pdf/2511.15948
==================================
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✓ https://t.iss.one/DataScienceT
#VideoUnderstanding #SceneGraphs #ComputerVision #InteractiveAI #AIResearch
📝 Summary:
Click2Graph is an interactive framework for Panoptic Video Scene Graph Generation. It uses a single user click to segment, track, discover interactions, and predict triplets for temporally consistent scene graphs. This enables user-guided, controllable video scene understanding.
🔹 Publication Date: Published on Nov 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.15948
• PDF: https://arxiv.org/pdf/2511.15948
==================================
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#VideoUnderstanding #SceneGraphs #ComputerVision #InteractiveAI #AIResearch
✨MG-Nav: Dual-Scale Visual Navigation via Sparse Spatial Memory
📝 Summary:
MG-Nav is a dual-scale framework for zero-shot visual navigation, unifying global memory-guided planning via a Sparse Spatial Memory Graph with local geometry-enhanced control using a VGGT-adapter. It achieves state-of-the-art performance and robustness in unseen environments.
🔹 Publication Date: Published on Nov 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.22609
• PDF: https://arxiv.org/pdf/2511.22609
==================================
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✓ https://t.iss.one/DataScienceT
#VisualNavigation #Robotics #AI #ComputerVision #ZeroShotLearning
📝 Summary:
MG-Nav is a dual-scale framework for zero-shot visual navigation, unifying global memory-guided planning via a Sparse Spatial Memory Graph with local geometry-enhanced control using a VGGT-adapter. It achieves state-of-the-art performance and robustness in unseen environments.
🔹 Publication Date: Published on Nov 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.22609
• PDF: https://arxiv.org/pdf/2511.22609
==================================
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#VisualNavigation #Robotics #AI #ComputerVision #ZeroShotLearning
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✨ViSAudio: End-to-End Video-Driven Binaural Spatial Audio Generation
📝 Summary:
ViSAudio is an end-to-end framework that generates high-quality binaural spatial audio directly from silent video. It uses conditional flow matching and a dual-branch architecture, outperforming previous methods in immersion and consistency. The paper also introduces the BiAudio dataset for this ...
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.03036
• PDF: https://arxiv.org/pdf/2512.03036
• Project Page: https://kszpxxzmc.github.io/ViSAudio-project/
• Github: https://github.com/kszpxxzmc/ViSAudio
==================================
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#SpatialAudio #AudioGeneration #DeepLearning #ComputerVision #AI
📝 Summary:
ViSAudio is an end-to-end framework that generates high-quality binaural spatial audio directly from silent video. It uses conditional flow matching and a dual-branch architecture, outperforming previous methods in immersion and consistency. The paper also introduces the BiAudio dataset for this ...
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.03036
• PDF: https://arxiv.org/pdf/2512.03036
• Project Page: https://kszpxxzmc.github.io/ViSAudio-project/
• Github: https://github.com/kszpxxzmc/ViSAudio
==================================
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#SpatialAudio #AudioGeneration #DeepLearning #ComputerVision #AI
✨MultiShotMaster: A Controllable Multi-Shot Video Generation Framework
📝 Summary:
MultiShotMaster is a framework for controllable multi-shot video generation. It extends a single-shot model with novel RoPE variants for flexible shot arrangement, narrative order, and spatiotemporal reference injection. The framework also uses an automated data annotation pipeline to address dat...
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.03041
• PDF: https://arxiv.org/pdf/2512.03041
• Project Page: https://qinghew.github.io/MultiShotMaster/
==================================
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#VideoGeneration #GenerativeAI #DeepLearning #AI #ComputerVision
📝 Summary:
MultiShotMaster is a framework for controllable multi-shot video generation. It extends a single-shot model with novel RoPE variants for flexible shot arrangement, narrative order, and spatiotemporal reference injection. The framework also uses an automated data annotation pipeline to address dat...
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.03041
• PDF: https://arxiv.org/pdf/2512.03041
• Project Page: https://qinghew.github.io/MultiShotMaster/
==================================
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#VideoGeneration #GenerativeAI #DeepLearning #AI #ComputerVision
✨C^2DLM: Causal Concept-Guided Diffusion Large Language Models
📝 Summary:
C2DLM is a Causal Concept-Guided Diffusion Language Model that improves reasoning. It guides DLM attention with concept-level causal graphs from a teacher model to learn causal relationships. This achieves an average gain of over one percent on reasoning tasks and speeds up training by 3.2 times.
🔹 Publication Date: Published on Nov 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.22146
• PDF: https://arxiv.org/pdf/2511.22146
==================================
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✓ https://t.iss.one/DataScienceT
#LLM #CausalAI #DiffusionModels #AI #NLP
📝 Summary:
C2DLM is a Causal Concept-Guided Diffusion Language Model that improves reasoning. It guides DLM attention with concept-level causal graphs from a teacher model to learn causal relationships. This achieves an average gain of over one percent on reasoning tasks and speeds up training by 3.2 times.
🔹 Publication Date: Published on Nov 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.22146
• PDF: https://arxiv.org/pdf/2511.22146
==================================
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✓ https://t.iss.one/DataScienceT
#LLM #CausalAI #DiffusionModels #AI #NLP
✨The Curious Case of Analogies: Investigating Analogical Reasoning in Large Language Models
📝 Summary:
LLMs can encode high-level relational concepts for analogies but struggle with missing relational information and transfer to new entities. Success depends on strong structural alignment. Their analogical reasoning is emerging but limited compared to humans.
🔹 Publication Date: Published on Nov 25
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.20344
• PDF: https://arxiv.org/pdf/2511.20344
==================================
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#LLMs #AnalogicalReasoning #AIResearch #NaturalLanguageProcessing #CognitiveAI
📝 Summary:
LLMs can encode high-level relational concepts for analogies but struggle with missing relational information and transfer to new entities. Success depends on strong structural alignment. Their analogical reasoning is emerging but limited compared to humans.
🔹 Publication Date: Published on Nov 25
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.20344
• PDF: https://arxiv.org/pdf/2511.20344
==================================
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✓ https://t.iss.one/DataScienceT
#LLMs #AnalogicalReasoning #AIResearch #NaturalLanguageProcessing #CognitiveAI
✨Artemis: Structured Visual Reasoning for Perception Policy Learning
📝 Summary:
Artemis improves visual perception by using structured spatial reasoning with label bounding-box pairs instead of linguistic intermediate reasoning. This avoids language ambiguity, enables direct supervision, and leads to strong performance and generalization across diverse visual tasks.
🔹 Publication Date: Published on Dec 1
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.01988
• PDF: https://arxiv.org/pdf/2512.01988
• Project Page: https://vi-ocean.github.io/projects/artemis/
• Github: https://github.com/WayneTomas/Artemis
==================================
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✓ https://t.iss.one/DataScienceT
#VisualPerception #ComputerVision #SpatialReasoning #AI #MachineLearning
📝 Summary:
Artemis improves visual perception by using structured spatial reasoning with label bounding-box pairs instead of linguistic intermediate reasoning. This avoids language ambiguity, enables direct supervision, and leads to strong performance and generalization across diverse visual tasks.
🔹 Publication Date: Published on Dec 1
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.01988
• PDF: https://arxiv.org/pdf/2512.01988
• Project Page: https://vi-ocean.github.io/projects/artemis/
• Github: https://github.com/WayneTomas/Artemis
==================================
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#VisualPerception #ComputerVision #SpatialReasoning #AI #MachineLearning
✨SimWorld: An Open-ended Realistic Simulator for Autonomous Agents in Physical and Social Worlds
📝 Summary:
SimWorld is a new Unreal Engine 5 simulator for developing and evaluating LLM VLM agents in realistic, open-ended physical and social environments. It provides diverse scenarios and a rich interface, revealing distinct reasoning patterns and limitations across frontier LLM models.
🔹 Publication Date: Published on Nov 30
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.01078
• PDF: https://arxiv.org/pdf/2512.01078
==================================
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✓ https://t.iss.one/DataScienceT
#AI #LLM #Simulation #AutonomousAgents #UnrealEngine5
📝 Summary:
SimWorld is a new Unreal Engine 5 simulator for developing and evaluating LLM VLM agents in realistic, open-ended physical and social environments. It provides diverse scenarios and a rich interface, revealing distinct reasoning patterns and limitations across frontier LLM models.
🔹 Publication Date: Published on Nov 30
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.01078
• PDF: https://arxiv.org/pdf/2512.01078
==================================
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✓ https://t.iss.one/DataScienceT
#AI #LLM #Simulation #AutonomousAgents #UnrealEngine5
✨CodeV: Code with Images for Faithful Visual Reasoning via Tool-Aware Policy Optimization
📝 Summary:
CodeV improves faithful visual reasoning by training an agent with Tool-Aware Policy Optimization TAPO. TAPO uses dense rewards directly on visual tool inputs and outputs, encouraging evidence-consistent tool use. This approach significantly boosts faithful tool use and achieves competitive accur...
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.19661
• PDF: https://arxiv.org/pdf/2511.19661
🔹 Models citing this paper:
• https://huggingface.co/RenlyH/CodeV-RL
• https://huggingface.co/RenlyH/CodeV-SFT
✨ Datasets citing this paper:
• https://huggingface.co/datasets/RenlyH/CodeV-RL-Data
==================================
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✓ https://t.iss.one/DataScienceT
#VisualReasoning #ReinforcementLearning #ComputerVision #AI #ToolLearning
📝 Summary:
CodeV improves faithful visual reasoning by training an agent with Tool-Aware Policy Optimization TAPO. TAPO uses dense rewards directly on visual tool inputs and outputs, encouraging evidence-consistent tool use. This approach significantly boosts faithful tool use and achieves competitive accur...
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.19661
• PDF: https://arxiv.org/pdf/2511.19661
🔹 Models citing this paper:
• https://huggingface.co/RenlyH/CodeV-RL
• https://huggingface.co/RenlyH/CodeV-SFT
✨ Datasets citing this paper:
• https://huggingface.co/datasets/RenlyH/CodeV-RL-Data
==================================
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✓ https://t.iss.one/DataScienceT
#VisualReasoning #ReinforcementLearning #ComputerVision #AI #ToolLearning
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✨Skywork-R1V4: Toward Agentic Multimodal Intelligence through Interleaved Thinking with Images and DeepResearch
📝 Summary:
Skywork-R1V4 is a 30B multimodal agentic model that unifies image manipulation and deep search with interleaved reasoning. It achieves state-of-the-art performance in perception and multimodal search using only supervised fine-tuning, demonstrating advanced intelligence without reinforcement lear...
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02395
• PDF: https://arxiv.org/pdf/2512.02395
• Project Page: https://docs.skyworkmodel.ai/r1v4/api-reference/completions.html
• Github: https://github.com/SkyworkAI/Skywork-R1V/tree/main/r1v4
🔹 Models citing this paper:
• https://huggingface.co/Skywork/R1V4
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #MultimodalAI #AgenticAI #DeepLearning #ComputerVision
📝 Summary:
Skywork-R1V4 is a 30B multimodal agentic model that unifies image manipulation and deep search with interleaved reasoning. It achieves state-of-the-art performance in perception and multimodal search using only supervised fine-tuning, demonstrating advanced intelligence without reinforcement lear...
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02395
• PDF: https://arxiv.org/pdf/2512.02395
• Project Page: https://docs.skyworkmodel.ai/r1v4/api-reference/completions.html
• Github: https://github.com/SkyworkAI/Skywork-R1V/tree/main/r1v4
🔹 Models citing this paper:
• https://huggingface.co/Skywork/R1V4
==================================
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✓ https://t.iss.one/DataScienceT
#AI #MultimodalAI #AgenticAI #DeepLearning #ComputerVision
✨CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning
📝 Summary:
CUDA-L2 uses LLMs and reinforcement learning to optimize Half-precision General Matrix Multiply CUDA kernels. It significantly outperforms major baselines like cuBLAS and torch.matmul, achieving up to 28.7% speedup in server mode. This demonstrates AI can enhance even highly optimized kernels.
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02551
• PDF: https://arxiv.org/pdf/2512.02551
• Github: https://github.com/deepreinforce-ai/CUDA-L2
==================================
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#CUDA #ReinforcementLearning #LLM #MatrixMultiplication #AI
📝 Summary:
CUDA-L2 uses LLMs and reinforcement learning to optimize Half-precision General Matrix Multiply CUDA kernels. It significantly outperforms major baselines like cuBLAS and torch.matmul, achieving up to 28.7% speedup in server mode. This demonstrates AI can enhance even highly optimized kernels.
🔹 Publication Date: Published on Dec 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.02551
• PDF: https://arxiv.org/pdf/2512.02551
• Github: https://github.com/deepreinforce-ai/CUDA-L2
==================================
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#CUDA #ReinforcementLearning #LLM #MatrixMultiplication #AI
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✨Masks Can Be Distracting: On Context Comprehension in Diffusion Language Models
📝 Summary:
Masked Diffusion Language Models MDLMs show locality bias and poor context comprehension due to appended mask tokens acting as distractors. A mask-agnostic loss function was introduced. This function improves MDLM robustness by mitigating the masks distracting effect.
🔹 Publication Date: Published on Nov 26
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.21338
• PDF: https://arxiv.org/pdf/2511.21338
==================================
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✓ https://t.iss.one/DataScienceT
#LanguageModels #DiffusionModels #NLP #ContextComprehension #AIResearch
📝 Summary:
Masked Diffusion Language Models MDLMs show locality bias and poor context comprehension due to appended mask tokens acting as distractors. A mask-agnostic loss function was introduced. This function improves MDLM robustness by mitigating the masks distracting effect.
🔹 Publication Date: Published on Nov 26
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.21338
• PDF: https://arxiv.org/pdf/2511.21338
==================================
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#LanguageModels #DiffusionModels #NLP #ContextComprehension #AIResearch
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