✨LoopCTR: Unlocking the Loop Scaling Power for Click-Through Rate Prediction
📝 Summary:
LoopCTR introduces a loop scaling paradigm for CTR models that increases training computation through recursive layer reuse while maintaining efficient inference, achieving state-of-the-art performanc...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19550
• PDF: https://arxiv.org/pdf/2604.19550
==================================
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📝 Summary:
LoopCTR introduces a loop scaling paradigm for CTR models that increases training computation through recursive layer reuse while maintaining efficient inference, achieving state-of-the-art performanc...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19550
• PDF: https://arxiv.org/pdf/2604.19550
==================================
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✨Target-Oriented Pretraining Data Selection via Neuron-Activated Graph
📝 Summary:
A novel target-oriented language model pretraining framework uses neuron activation graphs to select informative data without additional training, demonstrating superior performance across multiple be...
🔹 Publication Date: Published on Apr 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.15706
• PDF: https://arxiv.org/pdf/2604.15706
• Project Page: https://asillycat.github.io/NAG-website/
• Github: https://github.com/asillycat/NAG
==================================
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📝 Summary:
A novel target-oriented language model pretraining framework uses neuron activation graphs to select informative data without additional training, demonstrating superior performance across multiple be...
🔹 Publication Date: Published on Apr 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.15706
• PDF: https://arxiv.org/pdf/2604.15706
• Project Page: https://asillycat.github.io/NAG-website/
• Github: https://github.com/asillycat/NAG
==================================
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✨Tstars-Tryon 1.0: Robust and Realistic Virtual Try-On for Diverse Fashion Items
📝 Summary:
A commercial-scale virtual try-on system achieves high success rates, photorealistic results, and real-time performance through integrated system design and multi-stage training. AI-generated summary ...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19748
• PDF: https://arxiv.org/pdf/2604.19748
• Project Page: https://mpage.taobao.com/hd/download.html
==================================
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📝 Summary:
A commercial-scale virtual try-on system achieves high success rates, photorealistic results, and real-time performance through integrated system design and multi-stage training. AI-generated summary ...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19748
• PDF: https://arxiv.org/pdf/2604.19748
• Project Page: https://mpage.taobao.com/hd/download.html
==================================
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✨MM-JudgeBias: A Benchmark for Evaluating Compositional Biases in MLLM-as-a-Judge
📝 Summary:
Research identifies systematic biases in multimodal large language models used as automatic evaluators, revealing reliability issues and proposing a benchmark for measuring compositional bias through ...
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18164
• PDF: https://arxiv.org/pdf/2604.18164
• Project Page: https://mm-judgebias.github.io/
• Github: https://github.com/naver-ai/MM-JudgeBias
==================================
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📝 Summary:
Research identifies systematic biases in multimodal large language models used as automatic evaluators, revealing reliability issues and proposing a benchmark for measuring compositional bias through ...
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18164
• PDF: https://arxiv.org/pdf/2604.18164
• Project Page: https://mm-judgebias.github.io/
• Github: https://github.com/naver-ai/MM-JudgeBias
==================================
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✨ClawNet: Human-Symbiotic Agent Network for Cross-User Autonomous Cooperation
📝 Summary:
AI agents must evolve beyond individual task automation to enable secure, governed collaboration among multiple users through a human-symbiotic paradigm with identity-based governance mechanisms. AI-g...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19211
• PDF: https://arxiv.org/pdf/2604.19211
• Project Page: https://www.clawnet.hk/
==================================
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📝 Summary:
AI agents must evolve beyond individual task automation to enable secure, governed collaboration among multiple users through a human-symbiotic paradigm with identity-based governance mechanisms. AI-g...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19211
• PDF: https://arxiv.org/pdf/2604.19211
• Project Page: https://www.clawnet.hk/
==================================
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✨UniMesh: Unifying 3D Mesh Understanding and Generation
📝 Summary:
UniMesh presents a unified framework that combines 3D generation and understanding tasks through novel components including a Mesh Head, Chain of Mesh for iterative editing, and a self-reflection mech...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17472
• PDF: https://arxiv.org/pdf/2604.17472
• Project Page: https://aigeeksgroup.github.io/UniMesh/
• Github: https://github.com/AIGeeksGroup/UniMesh
==================================
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📝 Summary:
UniMesh presents a unified framework that combines 3D generation and understanding tasks through novel components including a Mesh Head, Chain of Mesh for iterative editing, and a self-reflection mech...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17472
• PDF: https://arxiv.org/pdf/2604.17472
• Project Page: https://aigeeksgroup.github.io/UniMesh/
• Github: https://github.com/AIGeeksGroup/UniMesh
==================================
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✨Evaluation-driven Scaling for Scientific Discovery
📝 Summary:
SimpleTES framework scales evaluation-driven discovery loops for scientific problems, achieving state-of-the-art results across multiple domains through parallel exploration and feedback-driven refine...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19341
• PDF: https://arxiv.org/pdf/2604.19341
• Project Page: https://www.wizardquant.com/will/simpletes
==================================
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📝 Summary:
SimpleTES framework scales evaluation-driven discovery loops for scientific problems, achieving state-of-the-art results across multiple domains through parallel exploration and feedback-driven refine...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19341
• PDF: https://arxiv.org/pdf/2604.19341
• Project Page: https://www.wizardquant.com/will/simpletes
==================================
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✨SPRITE: From Static Mockups to Engine-Ready Game UI
📝 Summary:
SPRITE enables automated conversion of game UI screenshots into editable engine assets by combining vision-language models with structured YAML representation to handle complex layouts and nesting. AI...
🔹 Publication Date: Published on Mar 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18591
• PDF: https://arxiv.org/pdf/2604.18591
• Project Page: https://baiyunshu.github.io/sprite.github.io/
==================================
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📝 Summary:
SPRITE enables automated conversion of game UI screenshots into editable engine assets by combining vision-language models with structured YAML representation to handle complex layouts and nesting. AI...
🔹 Publication Date: Published on Mar 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18591
• PDF: https://arxiv.org/pdf/2604.18591
• Project Page: https://baiyunshu.github.io/sprite.github.io/
==================================
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✨Chat2Workflow: A Benchmark for Generating Executable Visual Workflows with Natural Language
📝 Summary:
Chat2Workflow presents a benchmark and agentic framework for automating executable visual workflow generation from natural language, revealing significant challenges in achieving industrial-grade auto...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19667
• PDF: https://arxiv.org/pdf/2604.19667
• Github: https://github.com/zjunlp/Chat2Workflow
==================================
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📝 Summary:
Chat2Workflow presents a benchmark and agentic framework for automating executable visual workflow generation from natural language, revealing significant challenges in achieving industrial-grade auto...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19667
• PDF: https://arxiv.org/pdf/2604.19667
• Github: https://github.com/zjunlp/Chat2Workflow
==================================
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✨Speculative Decoding for Autoregressive Video Generation
📝 Summary:
Speculative decoding is adapted to autoregressive video diffusion through a quality-based routing mechanism that maintains high visual quality while achieving significant speedup. AI-generated summary...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17397
• PDF: https://arxiv.org/pdf/2604.17397
==================================
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📝 Summary:
Speculative decoding is adapted to autoregressive video diffusion through a quality-based routing mechanism that maintains high visual quality while achieving significant speedup. AI-generated summary...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17397
• PDF: https://arxiv.org/pdf/2604.17397
==================================
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✨Contrastive Attribution in the Wild: An Interpretability Analysis of LLM Failures on Realistic Benchmarks
📝 Summary:
Contrastive attribution methods for analyzing large language model failures show mixed effectiveness across different benchmarks and model sizes. AI-generated summary Interpretability tools are increa...
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17761
• PDF: https://arxiv.org/pdf/2604.17761
• Project Page: https://jzxycsjzy.github.io/Debug-XAI/
• Github: https://github.com/microsoft/Debug-XAI
==================================
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📝 Summary:
Contrastive attribution methods for analyzing large language model failures show mixed effectiveness across different benchmarks and model sizes. AI-generated summary Interpretability tools are increa...
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17761
• PDF: https://arxiv.org/pdf/2604.17761
• Project Page: https://jzxycsjzy.github.io/Debug-XAI/
• Github: https://github.com/microsoft/Debug-XAI
==================================
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✨TEMPO: Scaling Test-time Training for Large Reasoning Models
📝 Summary:
TEMPO is a test-time training framework that alternates policy refinement with critic recalibration to sustain performance improvements in language models without diversity collapse. AI-generated summ...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19295
• PDF: https://arxiv.org/pdf/2604.19295
• Project Page: https://qingyangzhang.github.io/tempo-homepage
• Github: https://github.com/QingyangZhang/TEMPO
==================================
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📝 Summary:
TEMPO is a test-time training framework that alternates policy refinement with critic recalibration to sustain performance improvements in language models without diversity collapse. AI-generated summ...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19295
• PDF: https://arxiv.org/pdf/2604.19295
• Project Page: https://qingyangzhang.github.io/tempo-homepage
• Github: https://github.com/QingyangZhang/TEMPO
==================================
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✨SmartPhotoCrafter: Unified Reasoning, Generation and Optimization for Automatic Photographic Image Editing
📝 Summary:
SmartPhotoCrafter automates photographic image editing by combining image quality comprehension with targeted enhancement, using a reasoning-to-generation approach that eliminates the need for explici...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19587
• PDF: https://arxiv.org/pdf/2604.19587
==================================
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📝 Summary:
SmartPhotoCrafter automates photographic image editing by combining image quality comprehension with targeted enhancement, using a reasoning-to-generation approach that eliminates the need for explici...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19587
• PDF: https://arxiv.org/pdf/2604.19587
==================================
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✨AnyRecon: Arbitrary-View 3D Reconstruction with Video Diffusion Model
📝 Summary:
AnyRecon enables scalable 3D reconstruction from arbitrary sparse inputs using diffusion models with persistent scene memory and geometry-aware conditioning for improved geometric consistency. AI-gene...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19747
• PDF: https://arxiv.org/pdf/2604.19747
🔹 Models citing this paper:
• https://huggingface.co/Yutian10/AnyRecon
==================================
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📝 Summary:
AnyRecon enables scalable 3D reconstruction from arbitrary sparse inputs using diffusion models with persistent scene memory and geometry-aware conditioning for improved geometric consistency. AI-gene...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19747
• PDF: https://arxiv.org/pdf/2604.19747
🔹 Models citing this paper:
• https://huggingface.co/Yutian10/AnyRecon
==================================
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✨Predicting integers from continuous parameters
📝 Summary:
Research examines direct modeling of integer-labeled data using discrete probability distributions with continuous parameters suitable for neural network training, evaluating Bitwise and discrete Lapl...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10751
• PDF: https://arxiv.org/pdf/2602.10751
==================================
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📝 Summary:
Research examines direct modeling of integer-labeled data using discrete probability distributions with continuous parameters suitable for neural network training, evaluating Bitwise and discrete Lapl...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10751
• PDF: https://arxiv.org/pdf/2602.10751
==================================
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✨UDM-GRPO: Stable and Efficient Group Relative Policy Optimization for Uniform Discrete Diffusion Models
📝 Summary:
UDM-GRPO integrates Uniform Discrete Diffusion Models with reinforcement learning, solving training instability issues. It optimizes using final samples as actions and reconstructed trajectories. This achieves state-of-the-art performance in text-to-image generation and OCR tasks.
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18518
• PDF: https://arxiv.org/pdf/2604.18518
• Project Page: https://yovecent.github.io/UDM-GRPO.github.io/
• Github: https://github.com/Yovecent/UDM-GRPO
🔹 Models citing this paper:
• https://huggingface.co/Yovecents/URSA-1.7B-IBQ512-UDMGRPO-GenEval
• https://huggingface.co/Yovecents/URSA-1.7B-IBQ512-UDMGRPO-PickScore
==================================
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📝 Summary:
UDM-GRPO integrates Uniform Discrete Diffusion Models with reinforcement learning, solving training instability issues. It optimizes using final samples as actions and reconstructed trajectories. This achieves state-of-the-art performance in text-to-image generation and OCR tasks.
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18518
• PDF: https://arxiv.org/pdf/2604.18518
• Project Page: https://yovecent.github.io/UDM-GRPO.github.io/
• Github: https://github.com/Yovecent/UDM-GRPO
🔹 Models citing this paper:
• https://huggingface.co/Yovecents/URSA-1.7B-IBQ512-UDMGRPO-GenEval
• https://huggingface.co/Yovecents/URSA-1.7B-IBQ512-UDMGRPO-PickScore
==================================
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❤1
✨Mitigating Multimodal Hallucination via Phase-wise Self-reward
📝 Summary:
PSRD is a new self-rewarding framework that mitigates vision hallucination in LVLMs dynamically during inference. It uses phase-wise self-reward signals and a lightweight reward model for efficient online correction, significantly reducing hallucination rates.
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17982
• PDF: https://arxiv.org/pdf/2604.17982
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📝 Summary:
PSRD is a new self-rewarding framework that mitigates vision hallucination in LVLMs dynamically during inference. It uses phase-wise self-reward signals and a lightweight reward model for efficient online correction, significantly reducing hallucination rates.
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17982
• PDF: https://arxiv.org/pdf/2604.17982
==================================
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✨The Cognitive Penalty: Ablating System 1 and System 2 Reasoning in Edge-Native SLMs for Decentralized Consensus
📝 Summary:
Research on SLMs in decentralized organizations finds that System 1 reasoning is superior for robust adversarial governance. System 2 inference-time compute introduces catastrophic instability, high latency, and vulnerabilities, making intuitive reasoning more effective.
🔹 Publication Date: Published on Apr 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.16913
• PDF: https://arxiv.org/pdf/2604.16913
• Github: https://github.com/smarizvi110/sentinel-bench
==================================
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📝 Summary:
Research on SLMs in decentralized organizations finds that System 1 reasoning is superior for robust adversarial governance. System 2 inference-time compute introduces catastrophic instability, high latency, and vulnerabilities, making intuitive reasoning more effective.
🔹 Publication Date: Published on Apr 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.16913
• PDF: https://arxiv.org/pdf/2604.16913
• Github: https://github.com/smarizvi110/sentinel-bench
==================================
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✨Chain-of-Thought Degrades Visual Spatial Reasoning Capabilities of Multimodal LLMs
📝 Summary:
Chain-of-Thought prompting in multimodal reasoning models degrades performance in visual spatial reasoning due to shortcut learning and hallucination of visual details from text alone. AI-generated su...
🔹 Publication Date: Published on Apr 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.16060
• PDF: https://arxiv.org/pdf/2604.16060
==================================
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📝 Summary:
Chain-of-Thought prompting in multimodal reasoning models degrades performance in visual spatial reasoning due to shortcut learning and hallucination of visual details from text alone. AI-generated su...
🔹 Publication Date: Published on Apr 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.16060
• PDF: https://arxiv.org/pdf/2604.16060
==================================
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❤1
✨Mind's Eye: A Benchmark of Visual Abstraction, Transformation and Composition for Multimodal LLMs
📝 Summary:
Multimodal large language models demonstrate significant limitations in visuospatial reasoning tasks compared to human performance, revealing deficiencies in visual attention, perceptual manipulation,...
🔹 Publication Date: Published on Apr 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.16054
• PDF: https://arxiv.org/pdf/2604.16054
==================================
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📝 Summary:
Multimodal large language models demonstrate significant limitations in visuospatial reasoning tasks compared to human performance, revealing deficiencies in visual attention, perceptual manipulation,...
🔹 Publication Date: Published on Apr 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.16054
• PDF: https://arxiv.org/pdf/2604.16054
==================================
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