✨The Blind Spot of Agent Safety: How Benign User Instructions Expose Critical Vulnerabilities in Computer-Use Agents

📝 Summary:
Computer-use agents face significant safety vulnerabilities under unintended attack conditions where benign instructions lead to harmful outcomes through contextual or execution-based risks, with atta...

🔹 Publication Date: Published on Apr 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10577
• PDF: https://arxiv.org/pdf/2604.10577
• Project Page: https://limenlp.github.io/OS_Blind/
• Github: https://github.com/limenlp/OS_Blind

✨ Datasets citing this paper:
• https://huggingface.co/datasets/lime-nlp/OS-Blind

==================================

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✨Seedance 2.0: Advancing Video Generation for World Complexity

📝 Summary:
Seedance 2.0 is a new multi-modal audio-video generation model supporting text, image, audio, and video inputs. It offers improved generation quality and speed through a unified architecture, performing on par with leading models. It generates 4-15 second content at 480p/720p.

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14148
• PDF: https://arxiv.org/pdf/2604.14148

==================================

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✨TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Exploration

📝 Summary:
A multi-agent system automates the complete lifecycle of large language model training by coordinating research and execution modules through iterative planning and experimentation. AI-generated summa...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14116
• PDF: https://arxiv.org/pdf/2604.14116
• Project Page: https://github.com/trex-project

==================================

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✨OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language World Models

📝 Summary:
OccuBench presents a comprehensive benchmark for evaluating AI agents across 100 professional domains using Language World Models to simulate real-world environments with controlled fault injection. A...

🔹 Publication Date: Published on Apr 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10866
• PDF: https://arxiv.org/pdf/2604.10866
• Project Page: https://gregxmhu.github.io/OccuBench-website/
• Github: https://github.com/GregxmHu/OccuBench

✨ Datasets citing this paper:
• https://huggingface.co/datasets/gregH/OccuBench

==================================

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✨UI-Zoomer: Uncertainty-Driven Adaptive Zoom-In for GUI Grounding

📝 Summary:
UI-Zoomer is a training-free adaptive zoom-in framework for GUI grounding that improves localization accuracy by selectively triggering zoom-in based on prediction uncertainty quantification. AI-gener...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14113
• PDF: https://arxiv.org/pdf/2604.14113
• Project Page: https://zju-real.github.io/UI-Zoomer/
• Github: https://github.com/ZJU-REAL/UI-Zoomer

==================================

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✨ROSE: Retrieval-Oriented Segmentation Enhancement

📝 Summary:
A new segmentation task focusing on novel and emerging entities is introduced along with a retrieval-augmented framework that enhances multimodal language models with real-time information and visual ...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14147
• PDF: https://arxiv.org/pdf/2604.14147
• Project Page: https://henghuiding.com/ROSE/

==================================

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✨InfiniteScienceGym: An Unbounded, Procedurally-Generated Benchmark for Scientific Analysis

📝 Summary:
InfiniteScienceGym presents a procedurally generated benchmark for evaluating scientific reasoning in language models, addressing limitations of traditional benchmarks through deterministic repository...

🔹 Publication Date: Published on Apr 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13201
• PDF: https://arxiv.org/pdf/2604.13201

==================================

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✨Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation

📝 Summary:
A self-distillation framework converts implicit 3D knowledge from video diffusion models into an explicit 3D Gaussian Splatting representation, enabling 3D scene generation from text or images. AI-gen...

🔹 Publication Date: Published on Sep 23, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.19296
• PDF: https://arxiv.org/pdf/2509.19296
• Project Page: https://research.nvidia.com/labs/toronto-ai/lyra/
• Github: https://github.com/nv-tlabs/lyra

🔹 Models citing this paper:
• https://huggingface.co/nvidia/Lyra

✨ Datasets citing this paper:
• https://huggingface.co/datasets/nvidia/PhysicalAI-SpatialIntelligence-Lyra-SDG

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✨SpatialEvo: Self-Evolving Spatial Intelligence via Deterministic Geometric Environments

📝 Summary:
SpatialEvo is a self-evolving framework for 3D spatial reasoning that uses deterministic geometric environments to provide objective feedback, enabling efficient training without relying on model cons...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14144
• PDF: https://arxiv.org/pdf/2604.14144
• Github: https://github.com/ZJU-REAL/SpatialEvo

🔹 Models citing this paper:
• https://huggingface.co/lidingm/SpatialEvo-3B
• https://huggingface.co/lidingm/SpatialEvo-7B

✨ Datasets citing this paper:
• https://huggingface.co/datasets/lidingm/SpatialEvo-160K

==================================

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✨TIP: Token Importance in On-Policy Distillation

📝 Summary:
On-policy knowledge distillation token selection methods are improved by identifying informative tokens through student entropy and teacher-student divergence, enabling efficient training with reduced...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14084
• PDF: https://arxiv.org/pdf/2604.14084
• Github: https://github.com/HJSang/OPSD_OnPolicyDistillation

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✨MERRIN: A Benchmark for Multimodal Evidence Retrieval and Reasoning in Noisy Web Environments

📝 Summary:
MERRIN is a human-annotated benchmark for evaluating search-augmented agents in multimodal, noisy web environments, demonstrating significant challenges in retrieving and reasoning over diverse eviden...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13418
• PDF: https://arxiv.org/pdf/2604.13418
• Project Page: https://merrin-benchmark.github.io
• Github: https://merrin-benchmark.github.io

✨ Datasets citing this paper:
• https://huggingface.co/datasets/HanNight/MERRIN

==================================

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✨UI-Copilot: Advancing Long-Horizon GUI Automation via Tool-Integrated Policy Optimization

📝 Summary:
UI-Copilot is a collaborative framework that enhances GUI agents by decoupling memory management and integrating on-demand tool assistance for improved performance in complex user interface tasks. AI-...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13822
• PDF: https://arxiv.org/pdf/2604.13822
• Github: https://github.com/ZJU-REAL/UI-Copilot

==================================

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✨RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time

📝 Summary:
Training reward models to generate multi-dimensional critiques improves visual generation through both enhanced reinforcement learning rewards and test-time refinement loops, achieving state-of-the-ar...

🔹 Publication Date: Published on Apr 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11626
• PDF: https://arxiv.org/pdf/2604.11626
• Project Page: https://tiger-ai-lab.github.io/RationalRewards/
• Github: https://github.com/TIGER-AI-Lab/RationalRewards

🔹 Models citing this paper:
• https://huggingface.co/TIGER-Lab/RationalRewards-8B-T2I
• https://huggingface.co/TIGER-Lab/RationalRewards-8B-Edit

✨ Datasets citing this paper:
• https://huggingface.co/datasets/TIGER-Lab/RationalRewards_DiffusionNFT_TrainData

==================================

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✨Free Geometry: Refining 3D Reconstruction from Longer Versions of Itself

📝 Summary:
Free Geometry enables feed-forward 3D reconstruction models to self-evolve at test time through self-supervised cross-view feature consistency, improving reconstruction accuracy with lightweight LoRA ...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14048
• PDF: https://arxiv.org/pdf/2604.14048
• Github: https://github.com/hiteacherIamhumble/Free-Geometry

==================================

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✨From P(y|x) to P(y): Investigating Reinforcement Learning in Pre-train Space

📝 Summary:
PreRL applies reward-driven online updates to the marginal distribution in pre-train space, while DSRL uses NSR-PreRL to expand reasoning horizons before standard RL fine-tuning. AI-generated summary ...

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14142
• PDF: https://arxiv.org/pdf/2604.14142
• Github: https://github.com/Trae1ounG/Pretrain_Space_RLVR

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✨Exploration and Exploitation Errors Are Measurable for Language Model Agents

📝 Summary:
Controllable environments with programmable exploration-exploitation balance are designed to evaluate language model agents' performance on embodied AI tasks, revealing distinct failure modes and demo...

🔹 Publication Date: Published on Apr 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13151
• PDF: https://arxiv.org/pdf/2604.13151
• Github: https://github.com/jjj-madison/measurable-explore-exploit

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✨Do AI Coding Agents Log Like Humans? An Empirical Study

📝 Summary:
S o f t w a r e l o g g i n g i s e s s e n t i a l f o r m a i n t a i n i n g a n d d e b u g g i n g c o m p l e x s y s t e m s , y e t i t r e m a i n s u n c l e a r h o w A I c o d i n g a g e ...

🔹 Publication Date: Published on Apr 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.09409
• PDF: https://arxiv.org/pdf/2604.09409

==================================

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✨Memory Transfer Learning: How Memories are Transferred Across Domains in Coding Agents

📝 Summary:
Memory Transfer Learning uses a unified memory pool from diverse coding domains to improve agent performance. It primarily transfers high-level meta-knowledge, not low-level code, showing that abstraction dictates effective cross-domain memory transfer.

🔹 Publication Date: Published on Apr 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.14004
• PDF: https://arxiv.org/pdf/2604.14004
• Project Page: https://memorytransfer.github.io/
• Github: https://github.com/KangsanKim07/MemoryTransferLearning

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✨Sema Code: Decoupling AI Coding Agents into Programmable, Embeddable Infrastructure

📝 Summary:
Sema Code presents an open AI coding framework that decouples the core agent engine from client interfaces, enabling shared reasoning capabilities across diverse development environments through a sta...

🔹 Publication Date: Published on Apr 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11045
• PDF: https://arxiv.org/pdf/2604.11045
• Github: https://github.com/midea-ai/SemaClaw

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✨ReconPhys: Reconstruct Appearance and Physical Attributes from Single Video

📝 Summary:
ReconPhys is the first feedforward framework to jointly learn physical attribute estimation and 3D Gaussian Splatting reconstruction from a single video. It offers significantly faster inference and superior reconstruction quality for non-rigid objects compared to prior optimization-based methods...

🔹 Publication Date: Published on Apr 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.07882
• PDF: https://arxiv.org/pdf/2604.07882
• Project Page: https://chuanshuogushi.github.io/ReconPhys/
• Github: https://chuanshuogushi.github.io/ReconPhys/

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✨SemaClaw: A Step Towards General-Purpose Personal AI Agents through Harness Engineering

📝 Summary:
SemaClaw is an open-source multi-agent framework addressing the need for robust infrastructure for personal AI agents. It ensures control and trustworthiness through novel orchestration, safety, and context management components, advancing general-purpose personal AI via harness engineering.

🔹 Publication Date: Published on Apr 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11548
• PDF: https://arxiv.org/pdf/2604.11548
• Github: https://github.com/midea-ai/sema-code-core

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