✨S0 Tuning: Zero-Overhead Adaptation of Hybrid Recurrent-Attention Models

📝 Summary:
S0 tuning optimizes recurrent state matrices in hybrid models, outperforming LoRA with zero inference overhead. It significantly improves performance on benchmarks like HumanEval and enables efficient task switching.

🔹 Publication Date: Published on Apr 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01168
• PDF: https://arxiv.org/pdf/2604.01168
• Project Page: https://www.jackyoung.io/research/s0-tuning
• Github: https://github.com/JackYoung27/s0-tuning

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#S0Tuning #DeepLearning #LLMs #ModelOptimization #MachineLearning

✨When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation

📝 Summary:
LLM agents struggle with user interruptions during long web navigation tasks. This paper introduces InterruptBench, the first systematic study and benchmark to evaluate interruptible agents in these scenarios. Results show that current LLMs find handling mid-task interruptions effectively and eff...

🔹 Publication Date: Published on Apr 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.00892
• PDF: https://arxiv.org/pdf/2604.00892
• Project Page: https://github.com/HenryPengZou/InterruptBench
• Github: https://github.com/HenryPengZou/InterruptBench

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#LLMAgents #UserInteractions #WebNavigation #AIResearch #Benchmarking

✨Consistency Amplifies: How Behavioral Variance Shapes Agent Accuracy

📝 Summary:
Behavioral consistency in LLM agents correlates with higher accuracy across models. However, consistency can amplify both correct and incorrect interpretations, meaning consistent wrong interpretations are a major failure mode. Thus, accurate interpretation is more crucial than execution consiste...

🔹 Publication Date: Published on Mar 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.25764
• PDF: https://arxiv.org/pdf/2603.25764

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

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#LLMAgents #ModelAccuracy #BehavioralAI #AIResearch #AIInterpretation

✨AgentWatcher: A Rule-based Prompt Injection Monitor

📝 Summary:
AgentWatcher defends LLMs against prompt injection, which struggles with long contexts and opaque detection. It achieves scalability by using causal attribution to pinpoint influential context segments. Detection is explainable through a monitor LLM that applies explicit rules.

🔹 Publication Date: Published on Apr 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01194
• PDF: https://arxiv.org/pdf/2604.01194
• Github: https://github.com/wang-yanting/AgentWatcher

🔹 Models citing this paper:
• https://huggingface.co/SecureLLMSys/AgentWatcher-Qwen3-4B-Instruct-2507

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨PixelPrune: Pixel-Level Adaptive Visual Token Reduction via Predictive Coding

📝 Summary:
PixelPrune reduces VLM computational costs by removing redundant image patches before Vision Transformer encoding. It uses predictive-coding compression in pixel space, speeding up inference and training up to 4.2x and 1.9x respectively while maintaining accuracy.

🔹 Publication Date: Published on Apr 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.00886
• PDF: https://arxiv.org/pdf/2604.00886
• Github: https://github.com/OPPO-Mente-Lab/PixelPrune

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨GPA: Learning GUI Process Automation from Demonstrations

📝 Summary:
GUI Process Automation (GPA) offers robust, deterministic, and privacy-preserving vision-based robotic process automation with faster execution than current vision-language model approaches. AI-genera...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01676
• PDF: https://arxiv.org/pdf/2604.01676
• Project Page: https://www.salesforceairesearch.com/gpa

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook

📝 Summary:
Latent space is emerging as a fundamental computational substrate for language-based models, offering advantages over explicit token-level approaches through continuous representation that mitigates l...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.02029
• PDF: https://arxiv.org/pdf/2604.02029
• Github: https://github.com/YU-deep/Awesome-Latent-Space

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization

📝 Summary:
SKILL0 enables LLM agents to internalize skills during training, allowing zero-shot autonomous behavior through a dynamic curriculum that reduces contextual overhead while improving task performance. ...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.02268
• PDF: https://arxiv.org/pdf/2604.02268
• Github: https://github.com/ZJU-REAL/SkillZero

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

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✨FlowSlider: Training-Free Continuous Image Editing via Fidelity-Steering Decomposition

📝 Summary:
FlowSlider enables continuous image editing with slider-style control by decomposing updates into fidelity and steering components within Rectified Flow, providing stable strength control without addi...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.02088
• PDF: https://arxiv.org/pdf/2604.02088
• Project Page: https://huggingface.co/spaces/dominoer/FlowSlider

✨ Spaces citing this paper:
• https://huggingface.co/spaces/dominoer/FlowSlider

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨DataFlex: A Unified Framework for Data-Centric Dynamic Training of Large Language Models

📝 Summary:
DataFlex is a unified framework for dynamic data-centric training of large language models that supports sample selection, domain mixture adjustment, and sample reweighting while maintaining compatibi...

🔹 Publication Date: Published on Mar 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.26164
• PDF: https://arxiv.org/pdf/2603.26164
• Github: https://github.com/OpenDCAI/DataFlex

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

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✨Generative World Renderer

📝 Summary:
A large-scale dynamic dataset derived from AAA games is introduced to improve generative inverse and forward rendering, featuring high-resolution synchronized RGB and G-buffer data alongside a novel V...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.02329
• PDF: https://arxiv.org/pdf/2604.02329
• Project Page: https://alaya-studio.github.io/renderer
• Github: https://github.com/ShandaAI/AlayaRenderer

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

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✨Omni-SimpleMem: Autoresearch-Guided Discovery of Lifelong Multimodal Agent Memory

📝 Summary:
An autonomous research pipeline discovers Omni-SimpleMem, a unified multimodal memory framework that significantly improves lifelong AI agent performance through automated architectural modifications,...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01007
• PDF: https://arxiv.org/pdf/2604.01007

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨EgoSim: Egocentric World Simulator for Embodied Interaction Generation

📝 Summary:
W e i n t r o d u c e E g o S i m , a c l o s e d - l o o p e g o c e n t r i c w o r l d s i m u l a t o r t h a t g e n e r a t e s s p a t i a l l y c o n s i s t e n t i n t e r a c t i o n v i d ...

🔹 Publication Date: Published on Apr 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01001
• PDF: https://arxiv.org/pdf/2604.01001
• Project Page: https://egosimulator.github.io/
• Github: https://egosimulator.github.io/

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨UniDriveVLA: Unifying Understanding, Perception, and Action Planning for Autonomous Driving

📝 Summary:
UniDriveVLA is a unified vision-language-action model for autonomous driving that decouples spatial perception and semantic reasoning through a mixture-of-transformers architecture with expert coordin...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.02190
• PDF: https://arxiv.org/pdf/2604.02190
• Project Page: https://xiaomi-research.github.io/unidrivevla/
• Github: https://github.com/xiaomi-research/unidrivevla

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨VideoZeroBench: Probing the Limits of Video MLLMs with Spatio-Temporal Evidence Verification

📝 Summary:
VideoZeroBench presents a comprehensive benchmark for long-video question answering with rigorous spatio-temporal evidence verification, revealing significant gaps in current models' grounded video un...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01569
• PDF: https://arxiv.org/pdf/2604.01569
• Project Page: https://marinero4972.github.io/projects/VideoZeroBench
• Github: https://github.com/marinero4972/VideoZeroBench

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

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✨Gated Condition Injection without Multimodal Attention: Towards Controllable Linear-Attention Transformers

📝 Summary:
Controllable diffusion models using linear attention architectures enable secure on-device visual generation with improved multi-condition input handling and faster convergence. AI-generated summary R...

🔹 Publication Date: Published on Mar 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.27666
• PDF: https://arxiv.org/pdf/2603.27666

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨LatentUM: Unleashing the Potential of Interleaved Cross-Modal Reasoning via a Latent-Space Unified Model

📝 Summary:
LatentUM is a unified model that represents all modalities in a shared semantic latent space, enabling efficient cross-modal reasoning and generation without pixel-space mediation. AI-generated summar...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.02097
• PDF: https://arxiv.org/pdf/2604.02097
• Github: https://github.com/SJTU-DENG-Lab/LatentUM

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

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✨Apriel-Reasoner: RL Post-Training for General-Purpose and Efficient Reasoning

📝 Summary:
Apriel-Reasoner, a 15B LLM, uses reproducible multi-domain RL post-training with novel sampling and length penalty to boost reasoning accuracy and efficiency. It achieves 30-50% shorter traces, outperforming its base model and matching peers at lower inference cost.

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.02007
• PDF: https://arxiv.org/pdf/2604.02007

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

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✨LinguDistill: Recovering Linguistic Ability in Vision- Language Models via Selective Cross-Modal Distillation

📝 Summary:
LinguDistill enables recovery of linguistic capabilities in vision-language models through adapter-free distillation using frozen language models as teachers, achieving performance close to pre-adapta...

🔹 Publication Date: Published on Apr 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.00829
• PDF: https://arxiv.org/pdf/2604.00829

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#VisionLanguageModels #NLP #ModelDistillation #ArtificialIntelligence #MachineLearning

✨Woosh: A Sound Effects Foundation Model

📝 Summary:
Woosh is a sound effect foundation model featuring audio encoding/decoding, text-audio alignment, and text-to-audio/video-to-audio generation capabilities with distilled versions for efficient deploym...

🔹 Publication Date: Published on Apr 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01929
• PDF: https://arxiv.org/pdf/2604.01929
• Project Page: https://sonyresearch.github.io/Woosh/
• Github: https://github.com/SonyResearch/Woosh

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✨Friends and Grandmothers in Silico: Localizing Entity Cells in Language Models

📝 Summary:
Entity-centric factual question answering involves localized MLP neurons that can be causally intervened to recover entity-consistent predictions, showing robustness to various linguistic variations b...

🔹 Publication Date: Published on Apr 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.01404
• PDF: https://arxiv.org/pdf/2604.01404
• Github: https://github.com/1tux/in-silico

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

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#AI #DataScience #MachineLearning #HuggingFace #Research