✨Coarse-Guided Visual Generation via Weighted h-Transform Sampling
📝 Summary:
This paper presents a novel training-free method for coarse-guided visual generation using h-transform to guide diffusion models. It modifies sampling transition probabilities with a drift function and employs a noise-level-aware schedule. This balances guidance adherence and high-quality synthes...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12057
• PDF: https://arxiv.org/pdf/2603.12057
• Github: https://github.com/HKUST-LongGroup/Coarse-guided-Gen
==================================
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📝 Summary:
This paper presents a novel training-free method for coarse-guided visual generation using h-transform to guide diffusion models. It modifies sampling transition probabilities with a drift function and employs a noise-level-aware schedule. This balances guidance adherence and high-quality synthes...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12057
• PDF: https://arxiv.org/pdf/2603.12057
• Github: https://github.com/HKUST-LongGroup/Coarse-guided-Gen
==================================
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✨NerVE: Nonlinear Eigenspectrum Dynamics in LLM Feed-Forward Networks
📝 Summary:
NerVE provides a unified framework for analyzing feed-forward network dynamics in large language models through spectral analysis metrics that reveal information flow organization and optimization imp...
🔹 Publication Date: Published on Mar 6
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.06922
• PDF: https://arxiv.org/pdf/2603.06922
• Project Page: https://nerve-eigenspectrum.github.io
==================================
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📝 Summary:
NerVE provides a unified framework for analyzing feed-forward network dynamics in large language models through spectral analysis metrics that reveal information flow organization and optimization imp...
🔹 Publication Date: Published on Mar 6
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.06922
• PDF: https://arxiv.org/pdf/2603.06922
• Project Page: https://nerve-eigenspectrum.github.io
==================================
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✨ShotVerse: Advancing Cinematic Camera Control for Text-Driven Multi-Shot Video Creation
📝 Summary:
ShotVerse introduces a plan-then-control framework for text-driven cinematic multi-shot video generation. It uses a VLM-based planner to generate camera trajectories and a controller for rendering them into video. Supported by a new calibrated dataset, ShotVerse-Bench, it achieves precise, consis...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11421
• PDF: https://arxiv.org/pdf/2603.11421
• Project Page: https://shotverse.github.io/
• Github: https://github.com/Songlin1998/ShotVerse
==================================
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📝 Summary:
ShotVerse introduces a plan-then-control framework for text-driven cinematic multi-shot video generation. It uses a VLM-based planner to generate camera trajectories and a controller for rendering them into video. Supported by a new calibrated dataset, ShotVerse-Bench, it achieves precise, consis...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11421
• PDF: https://arxiv.org/pdf/2603.11421
• Project Page: https://shotverse.github.io/
• Github: https://github.com/Songlin1998/ShotVerse
==================================
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✨WeEdit: A Dataset, Benchmark and Glyph-Guided Framework for Text-centric Image Editing
📝 Summary:
WeEdit presents a systematic approach for text-centric image editing with a scalable data pipeline, multi-language benchmarks, and a two-stage training strategy combining supervised fine-tuning and re...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11593
• PDF: https://arxiv.org/pdf/2603.11593
==================================
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📝 Summary:
WeEdit presents a systematic approach for text-centric image editing with a scalable data pipeline, multi-language benchmarks, and a two-stage training strategy combining supervised fine-tuning and re...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11593
• PDF: https://arxiv.org/pdf/2603.11593
==================================
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✨OmniStream: Mastering Perception, Reconstruction and Action in Continuous Streams
📝 Summary:
OmniStream is a unified visual backbone that processes streaming video data through causal spatiotemporal attention and 3D rotary positional embeddings, enabling general-purpose visual understanding a...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12265
• PDF: https://arxiv.org/pdf/2603.12265
• Project Page: https://go2heart.github.io/omnistream/
• Github: https://github.com/Go2Heart/OmniStream
==================================
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📝 Summary:
OmniStream is a unified visual backbone that processes streaming video data through causal spatiotemporal attention and 3D rotary positional embeddings, enabling general-purpose visual understanding a...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12265
• PDF: https://arxiv.org/pdf/2603.12265
• Project Page: https://go2heart.github.io/omnistream/
• Github: https://github.com/Go2Heart/OmniStream
==================================
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✨Trust Your Critic: Robust Reward Modeling and Reinforcement Learning for Faithful Image Editing and Generation
📝 Summary:
Reinforcement learning framework with novel reward modeling and benchmarking approaches improves fidelity and instruction adherence in image editing and text-to-image generation. AI-generated summary ...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12247
• PDF: https://arxiv.org/pdf/2603.12247
• Project Page: https://firm-reward.github.io/
• Github: https://github.com/VisionXLab/FIRM-Reward
==================================
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📝 Summary:
Reinforcement learning framework with novel reward modeling and benchmarking approaches improves fidelity and instruction adherence in image editing and text-to-image generation. AI-generated summary ...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12247
• PDF: https://arxiv.org/pdf/2603.12247
• Project Page: https://firm-reward.github.io/
• Github: https://github.com/VisionXLab/FIRM-Reward
==================================
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✨Strategic Navigation or Stochastic Search? How Agents and Humans Reason Over Document Collections
📝 Summary:
MADQA benchmark evaluates multimodal agents' strategic reasoning capabilities through diverse PDF document questions, revealing gaps between human-level accuracy and efficient reasoning performance. A...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12180
• PDF: https://arxiv.org/pdf/2603.12180
• Project Page: https://huggingface.co/spaces/Snowflake/MADQA-Leaderboard
• Github: https://github.com/OxRML/MADQA
✨ Datasets citing this paper:
• https://huggingface.co/datasets/OxRML/MADQA
✨ Spaces citing this paper:
• https://huggingface.co/spaces/Snowflake/MADQA-Leaderboard
==================================
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📝 Summary:
MADQA benchmark evaluates multimodal agents' strategic reasoning capabilities through diverse PDF document questions, revealing gaps between human-level accuracy and efficient reasoning performance. A...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12180
• PDF: https://arxiv.org/pdf/2603.12180
• Project Page: https://huggingface.co/spaces/Snowflake/MADQA-Leaderboard
• Github: https://github.com/OxRML/MADQA
✨ Datasets citing this paper:
• https://huggingface.co/datasets/OxRML/MADQA
✨ Spaces citing this paper:
• https://huggingface.co/spaces/Snowflake/MADQA-Leaderboard
==================================
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❤1
✨GRADE: Benchmarking Discipline-Informed Reasoning in Image Editing
📝 Summary:
GRADE is introduced as the first benchmark for assessing discipline-informed knowledge and reasoning in image editing, revealing significant limitations in current models under knowledge-intensive edi...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12264
• PDF: https://arxiv.org/pdf/2603.12264
• Project Page: https://grade-bench.github.io/
• Github: https://github.com/VisionXLab/GRADE
==================================
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📝 Summary:
GRADE is introduced as the first benchmark for assessing discipline-informed knowledge and reasoning in image editing, revealing significant limitations in current models under knowledge-intensive edi...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12264
• PDF: https://arxiv.org/pdf/2603.12264
• Project Page: https://grade-bench.github.io/
• Github: https://github.com/VisionXLab/GRADE
==================================
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✨EndoCoT: Scaling Endogenous Chain-of-Thought Reasoning in Diffusion Models
📝 Summary:
A novel framework called Endogenous Chain-of-Thought is proposed to enhance multimodal large language models' reasoning capabilities in diffusion frameworks by enabling iterative thought refinement an...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12252
• PDF: https://arxiv.org/pdf/2603.12252
• Project Page: https://internlm.github.io/EndoCoT/
• Github: https://github.com/InternLM/EndoCoT
==================================
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📝 Summary:
A novel framework called Endogenous Chain-of-Thought is proposed to enhance multimodal large language models' reasoning capabilities in diffusion frameworks by enabling iterative thought refinement an...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12252
• PDF: https://arxiv.org/pdf/2603.12252
• Project Page: https://internlm.github.io/EndoCoT/
• Github: https://github.com/InternLM/EndoCoT
==================================
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✨Spatial-TTT: Streaming Visual-based Spatial Intelligence with Test-Time Training
📝 Summary:
Spatial-TTT enables streaming visual-based spatial intelligence through test-time training that adapts parameters to capture spatial evidence over long video sequences using hybrid architecture and 3D...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12255
• PDF: https://arxiv.org/pdf/2603.12255
• Project Page: https://liuff19.github.io/Spatial-TTT/
• Github: https://github.com/THU-SI/Spatial-TTT
==================================
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📝 Summary:
Spatial-TTT enables streaming visual-based spatial intelligence through test-time training that adapts parameters to capture spatial evidence over long video sequences using hybrid architecture and 3D...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12255
• PDF: https://arxiv.org/pdf/2603.12255
• Project Page: https://liuff19.github.io/Spatial-TTT/
• Github: https://github.com/THU-SI/Spatial-TTT
==================================
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✨Tiny Aya: Bridging Scale and Multilingual Depth
📝 Summary:
Tiny Aya demonstrates high-quality multilingual capabilities with 3.35 billion parameters through region-aware posttraining and balanced language performance. AI-generated summary Tiny Aya redefines w...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11510
• PDF: https://arxiv.org/pdf/2603.11510
==================================
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📝 Summary:
Tiny Aya demonstrates high-quality multilingual capabilities with 3.35 billion parameters through region-aware posttraining and balanced language performance. AI-generated summary Tiny Aya redefines w...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11510
• PDF: https://arxiv.org/pdf/2603.11510
==================================
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✨Are Video Reasoning Models Ready to Go Outside?
📝 Summary:
ROVA is a training framework that enhances vision-language model robustness under real-world disturbances through spatio-temporal corruption modeling and adaptive sample difficulty assessment. AI-gene...
🔹 Publication Date: Published on Mar 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10652
• PDF: https://arxiv.org/pdf/2603.10652
• Project Page: https://robust-video-reason.github.io/
• Github: https://github.com/codepassionor/ROVA
==================================
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📝 Summary:
ROVA is a training framework that enhances vision-language model robustness under real-world disturbances through spatio-temporal corruption modeling and adaptive sample difficulty assessment. AI-gene...
🔹 Publication Date: Published on Mar 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10652
• PDF: https://arxiv.org/pdf/2603.10652
• Project Page: https://robust-video-reason.github.io/
• Github: https://github.com/codepassionor/ROVA
==================================
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✨Geometric Autoencoder for Diffusion Models
📝 Summary:
Geometric Autoencoder (GAE) presents a principled approach to latent diffusion modeling by optimizing semantic supervision, latent manifold stability, and reconstruction robustness through geometric a...
🔹 Publication Date: Published on Mar 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10365
• PDF: https://arxiv.org/pdf/2603.10365
• Project Page: https://huggingface.co/sii-research/gae-imagenet256-f16d32
• Github: https://github.com/sii-research/GAE
🔹 Models citing this paper:
• https://huggingface.co/GK50/GAE-Checkpoints
• https://huggingface.co/sii-research/gae-imagenet256-f16d32
==================================
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📝 Summary:
Geometric Autoencoder (GAE) presents a principled approach to latent diffusion modeling by optimizing semantic supervision, latent manifold stability, and reconstruction robustness through geometric a...
🔹 Publication Date: Published on Mar 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10365
• PDF: https://arxiv.org/pdf/2603.10365
• Project Page: https://huggingface.co/sii-research/gae-imagenet256-f16d32
• Github: https://github.com/sii-research/GAE
🔹 Models citing this paper:
• https://huggingface.co/GK50/GAE-Checkpoints
• https://huggingface.co/sii-research/gae-imagenet256-f16d32
==================================
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✨Video-Based Reward Modeling for Computer-Use Agents
📝 Summary:
Video-execution reward modeling enables scalable evaluation of computer-using agents by predicting task success from user instructions and execution videos, outperforming proprietary models across mul...
🔹 Publication Date: Published on Mar 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10178
• PDF: https://arxiv.org/pdf/2603.10178
• Github: https://github.com/limenlp/ExeVRM
🔹 Models citing this paper:
• https://huggingface.co/lime-nlp/ExeVRM-8B
✨ Datasets citing this paper:
• https://huggingface.co/datasets/lime-nlp/ExeVR-53k
==================================
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📝 Summary:
Video-execution reward modeling enables scalable evaluation of computer-using agents by predicting task success from user instructions and execution videos, outperforming proprietary models across mul...
🔹 Publication Date: Published on Mar 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10178
• PDF: https://arxiv.org/pdf/2603.10178
• Github: https://github.com/limenlp/ExeVRM
🔹 Models citing this paper:
• https://huggingface.co/lime-nlp/ExeVRM-8B
✨ Datasets citing this paper:
• https://huggingface.co/datasets/lime-nlp/ExeVR-53k
==================================
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✨TeamHOI: Learning a Unified Policy for Cooperative Human-Object Interactions with Any Team Size
📝 Summary:
TeamHOI enables decentralized cooperative human-object interaction using a Transformer-based policy with teammate tokens and a masked adversarial motion prior for realistic multi-agent coordination. A...
🔹 Publication Date: Published on Mar 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07988
• PDF: https://arxiv.org/pdf/2603.07988
• Project Page: https://splionar.github.io/TeamHOI/
• Github: https://github.com/sail-sg/TeamHOI
==================================
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📝 Summary:
TeamHOI enables decentralized cooperative human-object interaction using a Transformer-based policy with teammate tokens and a masked adversarial motion prior for realistic multi-agent coordination. A...
🔹 Publication Date: Published on Mar 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07988
• PDF: https://arxiv.org/pdf/2603.07988
• Project Page: https://splionar.github.io/TeamHOI/
• Github: https://github.com/sail-sg/TeamHOI
==================================
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✨SoundWeaver: Semantic Warm-Starting for Text-to-Audio Diffusion Serving
📝 Summary:
SoundWeaver accelerates text-to-audio diffusion generation by caching semantically similar audio and dynamically skipping function evaluations, achieving significant latency reduction with minimal qua...
🔹 Publication Date: Published on Mar 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07865
• PDF: https://arxiv.org/pdf/2603.07865
==================================
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📝 Summary:
SoundWeaver accelerates text-to-audio diffusion generation by caching semantically similar audio and dynamically skipping function evaluations, achieving significant latency reduction with minimal qua...
🔹 Publication Date: Published on Mar 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07865
• PDF: https://arxiv.org/pdf/2603.07865
==================================
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✨DreamVideo-Omni: Omni-Motion Controlled Multi-Subject Video Customization with Latent Identity Reinforcement Learning
📝 Summary:
DreamVideo-Omni is a unified framework for video synthesis that enables precise multi-subject identity control and multi-granularity motion manipulation through a two-stage training approach combining...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12257
• PDF: https://arxiv.org/pdf/2603.12257
• Project Page: https://dreamvideo-omni.github.io/
• Github: https://dreamvideo-omni.github.io/
==================================
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📝 Summary:
DreamVideo-Omni is a unified framework for video synthesis that enables precise multi-subject identity control and multi-granularity motion manipulation through a two-stage training approach combining...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12257
• PDF: https://arxiv.org/pdf/2603.12257
• Project Page: https://dreamvideo-omni.github.io/
• Github: https://dreamvideo-omni.github.io/
==================================
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✨Examining Reasoning LLMs-as-Judges in Non-Verifiable LLM Post-Training
📝 Summary:
Research examines the effectiveness of reasoning versus non-reasoning large language model judges in reinforcement learning-based alignment, revealing that reasoning judges prevent reward hacking but ...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12246
• PDF: https://arxiv.org/pdf/2603.12246
==================================
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📝 Summary:
Research examines the effectiveness of reasoning versus non-reasoning large language model judges in reinforcement learning-based alignment, revealing that reasoning judges prevent reward hacking but ...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12246
• PDF: https://arxiv.org/pdf/2603.12246
==================================
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✨One Model, Many Budgets: Elastic Latent Interfaces for Diffusion Transformers
📝 Summary:
Elastic Latent Interface Transformer (ELIT) decouples compute from image resolution in diffusion transformers by introducing learnable latent tokens that adaptively prioritize important regions, enabl...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12245
• PDF: https://arxiv.org/pdf/2603.12245
• Project Page: https://snap-research.github.io/elit/
==================================
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📝 Summary:
Elastic Latent Interface Transformer (ELIT) decouples compute from image resolution in diffusion transformers by introducing learnable latent tokens that adaptively prioritize important regions, enabl...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.12245
• PDF: https://arxiv.org/pdf/2603.12245
• Project Page: https://snap-research.github.io/elit/
==================================
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✨Multi-Task Reinforcement Learning for Enhanced Multimodal LLM-as-a-Judge
📝 Summary:
Multi-Task Reinforcement Learning framework improves multimodal large language models' judgment consistency and generalization across diverse visual tasks. AI-generated summary Multimodal Large Langua...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11665
• PDF: https://arxiv.org/pdf/2603.11665
==================================
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📝 Summary:
Multi-Task Reinforcement Learning framework improves multimodal large language models' judgment consistency and generalization across diverse visual tasks. AI-generated summary Multimodal Large Langua...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11665
• PDF: https://arxiv.org/pdf/2603.11665
==================================
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✨Attention Sinks Are Provably Necessary in Softmax Transformers: Evidence from Trigger-Conditional Tasks
📝 Summary:
Softmax self-attention models exhibit attention sinks where probability mass concentrates on fixed positions due to normalization constraints, while ReLU attention avoids this behavior. AI-generated s...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11487
• PDF: https://arxiv.org/pdf/2603.11487
• Github: https://github.com/YuvMilo/sinks-are-provably-necessary
==================================
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📝 Summary:
Softmax self-attention models exhibit attention sinks where probability mass concentrates on fixed positions due to normalization constraints, while ReLU attention avoids this behavior. AI-generated s...
🔹 Publication Date: Published on Mar 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11487
• PDF: https://arxiv.org/pdf/2603.11487
• Github: https://github.com/YuvMilo/sinks-are-provably-necessary
==================================
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