✨Forge-UGC: FX optimization and register-graph engine for universal graph compiler
📝 Summary:
Forge-UGC is a four-phase compiler for efficient transformer deployment on heterogeneous hardware, offering faster compilation, reduced inference latency, and lower energy consumption compared to exis...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.16498
• PDF: https://arxiv.org/pdf/2604.16498
==================================
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📝 Summary:
Forge-UGC is a four-phase compiler for efficient transformer deployment on heterogeneous hardware, offering faster compilation, reduced inference latency, and lower energy consumption compared to exis...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.16498
• PDF: https://arxiv.org/pdf/2604.16498
==================================
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✨Protecting Language Models Against Unauthorized Distillation through Trace Rewriting
📝 Summary:
Techniques for modifying teacher-generated reasoning traces to prevent unauthorized knowledge distillation while maintaining answer correctness and enabling detectable watermarks are presented. AI-gen...
🔹 Publication Date: Published on Apr 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.15143
• PDF: https://arxiv.org/pdf/2602.15143
• Github: https://github.com/xhOwenMa/trace-rewriting
==================================
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📝 Summary:
Techniques for modifying teacher-generated reasoning traces to prevent unauthorized knowledge distillation while maintaining answer correctness and enabling detectable watermarks are presented. AI-gen...
🔹 Publication Date: Published on Apr 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.15143
• PDF: https://arxiv.org/pdf/2602.15143
• Github: https://github.com/xhOwenMa/trace-rewriting
==================================
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✨Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility
📝 Summary:
Symbolic guardrails provide strong safety and security guarantees for AI agents in high-stakes environments. A study found these guardrails can enforce 74% of specified policy requirements, improving safety without sacrificing utility. This makes them a practical solution for domain-specific agents.
🔹 Publication Date: Published on Apr 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.15579
• PDF: https://arxiv.org/pdf/2604.15579
• Github: https://github.com/hyn0027/agent-symbolic-guardrails
✨ Datasets citing this paper:
• https://huggingface.co/datasets/hyn0027D/agent-symbolic-guardrails
==================================
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📝 Summary:
Symbolic guardrails provide strong safety and security guarantees for AI agents in high-stakes environments. A study found these guardrails can enforce 74% of specified policy requirements, improving safety without sacrificing utility. This makes them a practical solution for domain-specific agents.
🔹 Publication Date: Published on Apr 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.15579
• PDF: https://arxiv.org/pdf/2604.15579
• Github: https://github.com/hyn0027/agent-symbolic-guardrails
✨ Datasets citing this paper:
• https://huggingface.co/datasets/hyn0027D/agent-symbolic-guardrails
==================================
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✨When Background Matters: Breaking Medical Vision Language Models by Transferable Attack
📝 Summary:
MedFocusLeak enables transferable black-box attacks on vision-language models for medical imaging by injecting imperceptible perturbations that redirect model attention, demonstrating significant vuln...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17318
• PDF: https://arxiv.org/pdf/2604.17318
• Project Page: https://akashghosh.github.io/MedFocusLeakACL/
• Github: https://github.com/AkashGhosh/When-Background-Matters-Breaking-Medical-Vision-Language-Models-by-Transferable-Attack
==================================
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📝 Summary:
MedFocusLeak enables transferable black-box attacks on vision-language models for medical imaging by injecting imperceptible perturbations that redirect model attention, demonstrating significant vuln...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17318
• PDF: https://arxiv.org/pdf/2604.17318
• Project Page: https://akashghosh.github.io/MedFocusLeakACL/
• Github: https://github.com/AkashGhosh/When-Background-Matters-Breaking-Medical-Vision-Language-Models-by-Transferable-Attack
==================================
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✨MARCO: Navigating the Unseen Space of Semantic Correspondence
📝 Summary:
MARCO is a compact, fast model for semantic correspondence that excels at generalizing to unseen keypoints. Its coarse-to-fine objective and self-distillation framework improve fine-grained localization and overall accuracy.
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18267
• PDF: https://arxiv.org/pdf/2604.18267
• Project Page: https://visinf.github.io/MARCO
• Github: https://github.com/visinf/MARCO
==================================
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📝 Summary:
MARCO is a compact, fast model for semantic correspondence that excels at generalizing to unseen keypoints. Its coarse-to-fine objective and self-distillation framework improve fine-grained localization and overall accuracy.
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18267
• PDF: https://arxiv.org/pdf/2604.18267
• Project Page: https://visinf.github.io/MARCO
• Github: https://github.com/visinf/MARCO
==================================
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✨River-LLM: Large Language Model Seamless Exit Based on KV Share
📝 Summary:
River-LLM enables efficient token-level early exit in LLMs by introducing a KV-Shared Exit River. This mechanism naturally generates and preserves missing historical states, overcoming the KV Cache Absence problem. It achieves 1.71 to 2.16 times practical speedup while maintaining high generation...
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18396
• PDF: https://arxiv.org/pdf/2604.18396
==================================
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📝 Summary:
River-LLM enables efficient token-level early exit in LLMs by introducing a KV-Shared Exit River. This mechanism naturally generates and preserves missing historical states, overcoming the KV Cache Absence problem. It achieves 1.71 to 2.16 times practical speedup while maintaining high generation...
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18396
• PDF: https://arxiv.org/pdf/2604.18396
==================================
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✨Terminal Wrench: A Dataset of 331 Reward-Hackable Environments and 3,632 Exploit Trajectories
📝 Summary:
A dataset of 331 terminal-agent environments with 3,632 reward-hacking trajectories and 2,352 legitimate baselines across four AI models is released to study adversarial exploits in system administrat...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17596
• PDF: https://arxiv.org/pdf/2604.17596
• Project Page: https://github.com/few-sh/terminal-wrench
• Github: https://github.com/few-sh/terminal-wrench
==================================
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📝 Summary:
A dataset of 331 terminal-agent environments with 3,632 reward-hacking trajectories and 2,352 legitimate baselines across four AI models is released to study adversarial exploits in system administrat...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17596
• PDF: https://arxiv.org/pdf/2604.17596
• Project Page: https://github.com/few-sh/terminal-wrench
• Github: https://github.com/few-sh/terminal-wrench
==================================
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✨KWBench: Measuring Unprompted Problem Recognition in Knowledge Work
📝 Summary:
KWBench is a new benchmark for evaluating LLMs ability to recognize underlying game-theoretic structures in professional scenarios without prompts. It tests if models can identify the problem type from raw inputs alone. Current LLMs perform poorly, failing to recognize problems even if they can a...
🔹 Publication Date: Published on Apr 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.15760
• PDF: https://arxiv.org/pdf/2604.15760
• Project Page: https://kwbench.github.io/
• Github: https://github.com/ankitmaloo/fasteval
==================================
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📝 Summary:
KWBench is a new benchmark for evaluating LLMs ability to recognize underlying game-theoretic structures in professional scenarios without prompts. It tests if models can identify the problem type from raw inputs alone. Current LLMs perform poorly, failing to recognize problems even if they can a...
🔹 Publication Date: Published on Apr 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.15760
• PDF: https://arxiv.org/pdf/2604.15760
• Project Page: https://kwbench.github.io/
• Github: https://github.com/ankitmaloo/fasteval
==================================
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✨AgentSPEX: An Agent SPecification and EXecution Language
📝 Summary:
AgentSPEX is a domain-specific language and framework for creating structured, modular, and interpretable large language model agent workflows with explicit control flow and state management. AI-gener...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13346
• PDF: https://arxiv.org/pdf/2604.13346
• Project Page: https://agentspex.ai/
• Github: https://github.com/ScaleML/AgentSPEX
==================================
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📝 Summary:
AgentSPEX is a domain-specific language and framework for creating structured, modular, and interpretable large language model agent workflows with explicit control flow and state management. AI-gener...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13346
• PDF: https://arxiv.org/pdf/2604.13346
• Project Page: https://agentspex.ai/
• Github: https://github.com/ScaleML/AgentSPEX
==================================
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✨CoInteract: Physically-Consistent Human-Object Interaction Video Synthesis via Spatially-Structured Co-Generation
📝 Summary:
CoInteract presents an end-to-end framework for human-object interaction video synthesis using a Diffusion Transformer backbone with specialized modules for structural stability and physical plausibil...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19636
• PDF: https://arxiv.org/pdf/2604.19636
• Project Page: https://xinxiaozhe12345.github.io/CoInteract_Project/
• Github: https://github.com/luoxyhappy/CoInteract
🔹 Models citing this paper:
• https://huggingface.co/georgexin/cointeract
==================================
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📝 Summary:
CoInteract presents an end-to-end framework for human-object interaction video synthesis using a Diffusion Transformer backbone with specialized modules for structural stability and physical plausibil...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19636
• PDF: https://arxiv.org/pdf/2604.19636
• Project Page: https://xinxiaozhe12345.github.io/CoInteract_Project/
• Github: https://github.com/luoxyhappy/CoInteract
🔹 Models citing this paper:
• https://huggingface.co/georgexin/cointeract
==================================
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✨PlayCoder: Making LLM-Generated GUI Code Playable
📝 Summary:
Large language models struggle to generate logically correct GUI applications, prompting the development of PlayEval benchmark and PlayCoder framework that uses multi-agent approaches to improve funct...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19742
• PDF: https://arxiv.org/pdf/2604.19742
• Project Page: https://arxiv.org/abs/2604.19742
• Github: https://github.com/Tencent/PlayCoder
==================================
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📝 Summary:
Large language models struggle to generate logically correct GUI applications, prompting the development of PlayEval benchmark and PlayCoder framework that uses multi-agent approaches to improve funct...
🔹 Publication Date: Published on Apr 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.19742
• PDF: https://arxiv.org/pdf/2604.19742
• Project Page: https://arxiv.org/abs/2604.19742
• Github: https://github.com/Tencent/PlayCoder
==================================
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✨Dual-View Training for Instruction-Following Information Retrieval
📝 Summary:
A dual-view data synthesis approach using polarity reversal enhances retrieval systems' ability to follow instructions by training models to distinguish between topic-relevant and instruction-complian...
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18845
• PDF: https://arxiv.org/pdf/2604.18845
==================================
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📝 Summary:
A dual-view data synthesis approach using polarity reversal enhances retrieval systems' ability to follow instructions by training models to distinguish between topic-relevant and instruction-complian...
🔹 Publication Date: Published on Apr 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.18845
• PDF: https://arxiv.org/pdf/2604.18845
==================================
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✨Code-Switching Information Retrieval: Benchmarks, Analysis, and the Limits of Current Retrievers
📝 Summary:
Code-switching poses significant challenges for information retrieval systems, revealing performance bottlenecks and embedding space divergences that current multilingual approaches cannot fully addre...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17632
• PDF: https://arxiv.org/pdf/2604.17632
• Github: https://github.com/paddler2022/Code-Switching-Information-Retrieval
==================================
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📝 Summary:
Code-switching poses significant challenges for information retrieval systems, revealing performance bottlenecks and embedding space divergences that current multilingual approaches cannot fully addre...
🔹 Publication Date: Published on Apr 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.17632
• PDF: https://arxiv.org/pdf/2604.17632
• Github: https://github.com/paddler2022/Code-Switching-Information-Retrieval
==================================
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✨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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