✨The Sonar Moment: Benchmarking Audio-Language Models in Audio Geo-Localization

📝 Summary:
Audio geo-localization benchmark AGL1K is introduced to advance audio language models' geospatial reasoning capabilities through curated audio clips and evaluation across multiple models. AI-generated...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03227
• PDF: https://arxiv.org/pdf/2601.03227
• Github: https://github.com/Rising0321/AGL1K

✨ Spaces citing this paper:
• https://huggingface.co/spaces/RisingZhang/AudioGeoLoc

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#AI #DataScience #MachineLearning #HuggingFace #Research

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✨SOP: A Scalable Online Post-Training System for Vision-Language-Action Models

📝 Summary:
SOP is a scalable online post-training system for VLA models that enables real-world robot policy adaptation. It uses a robot fleet to continuously learn from interaction, improving task proficiency while maintaining generality. SOP significantly boosts VLA model performance within hours.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03044
• PDF: https://arxiv.org/pdf/2601.03044

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✨SciEvalKit: An Open-source Evaluation Toolkit for Scientific General Intelligence

📝 Summary:
SciEvalKit is an open-source toolkit for evaluating AI models in science. It assesses scientific intelligence across diverse domains and competencies using expert-grade benchmarks and a flexible pipeline. This provides a standardized platform for scientific AI evaluation.

🔹 Publication Date: Published on Dec 26, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.22334
• PDF: https://arxiv.org/pdf/2512.22334

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#AIevaluation #ScientificAI #OpenSource #AIBenchmarks #AIResearch

✨Steerability of Instrumental-Convergence Tendencies in LLMs

📝 Summary:
This research investigates AI system steerability, noting a safety-security dilemma. It demonstrates that a short anti-instrumental prompt suffix dramatically reduces unwanted instrumental behaviors, like self-replication, in large language models. For Qwen3-30B, this reduced the convergence rate...

🔹 Publication Date: Published on Jan 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01584
• PDF: https://arxiv.org/pdf/2601.01584
• Github: https://github.com/j-hoscilowicz/instrumental_steering/

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#AISafety #LLMs #AISteering #PromptEngineering #AIAlignment

✨OpenRT: An Open-Source Red Teaming Framework for Multimodal LLMs

📝 Summary:
OpenRT is an open-source framework that unifies and modularizes red-teaming for multimodal LLMs. It exposes significant safety gaps in frontier models, which fail to generalize across diverse attacks, showing attack success rates up to 49.14%.

🔹 Publication Date: Published on Jan 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01592
• PDF: https://arxiv.org/pdf/2601.01592
• Project Page: https://ai45lab.github.io/OpenRT/
• Github: https://github.com/AI45Lab/OpenRT

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#RedTeaming #MultimodalLLMs #AISafety #LLMSecurity #AIResearch

✨AceFF: A State-of-the-Art Machine Learning Potential for Small Molecules

📝 Summary:
AceFF is a new machine learning potential for small molecule drug discovery. It offers DFT-level accuracy with high speed, supporting essential elements and charged states. Validation shows it is state-of-the-art for organic molecules.

🔹 Publication Date: Published on Jan 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.00581
• PDF: https://arxiv.org/pdf/2601.00581
• Github: https://github.com/torchmd/torchmd-net

🔹 Models citing this paper:
• https://huggingface.co/Acellera/AceFF-2.0

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

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#MachineLearning #DrugDiscovery #ComputationalChemistry #AIforScience #SmallMolecules

✨Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training

📝 Summary:
Muses is a training-free method for generating fantastic 3D creatures. It leverages 3D skeletal structures and graph-constrained reasoning to coherently design, compose, and assemble diverse elements. This approach achieves state-of-the-art visual fidelity and alignment with text descriptions.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03256
• PDF: https://arxiv.org/pdf/2601.03256
• Github: https://github.com/luhexiao/Muses

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

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#3DGeneration #GenerativeAI #ComputerGraphics #AIArt #TrainingFreeAI

✨U-Net-Like Spiking Neural Networks for Single Image Dehazing

📝 Summary:
DehazeSNN introduces a U-Net-like Spiking Neural Network with an Orthogonal Leaky-Integrate-and-Fire Block for efficient image dehazing. It achieves competitive performance with reduced computational resources and a smaller model size.

🔹 Publication Date: Published on Dec 30, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.23950
• PDF: https://arxiv.org/pdf/2512.23950
• Github: https://github.com/HaoranLiu507/DehazeSNN

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Digital Twin AI: Opportunities and Challenges from Large Language Models to World Models

📝 Summary:
This paper presents a four-stage framework for AI in digital twins: modeling, mirroring, intervention, and autonomous management. It details how physics-informed AI and large language models empower proactive, self-improving digital twins, acknowledging key challenges.

🔹 Publication Date: Published on Jan 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01321
• PDF: https://arxiv.org/pdf/2601.01321
• Github: https://github.com/rongzhou7/Awesome-Digital-Twin-AI/tree/main

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#DigitalTwin #AI #LLM #WorldModels #PhysicsInformedAI

✨Mechanistic Interpretability of Large-Scale Counting in LLMs through a System-2 Strategy

📝 Summary:
LLMs struggle with large counting due to architectural limits. A System-2 inspired test-time strategy decomposes tasks into smaller parts, achieving high accuracy. This approach involves latent count computation, dedicated attention, and aggregation, overcoming model limitations.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02989
• PDF: https://arxiv.org/pdf/2601.02989

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

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#LLM #MechanisticInterpretability #System2Strategy #AIResearch #NLP

✨ExposeAnyone: Personalized Audio-to-Expression Diffusion Models Are Robust Zero-Shot Face Forgery Detectors

📝 Summary:
ExposeAnyone is a self-supervised diffusion model for deepfake detection that personalizes to subjects and uses reconstruction errors to measure identity distance. It significantly outperforms prior methods on unseen manipulations, including Sora2 videos, and is robust to real-world corruptions.

🔹 Publication Date: Published on Jan 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02359
• PDF: https://arxiv.org/pdf/2601.02359
• Github: https://mapooon.github.io/ExposeAnyonePage/

✨ Datasets citing this paper:
• https://huggingface.co/datasets/mapooon/S2CFP

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

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#DeepfakeDetection #DiffusionModels #ComputerVision #AITechnology #ForgeryDetection

✨Unified Thinker: A General Reasoning Modular Core for Image Generation

📝 Summary:
Unified Thinker introduces a modular reasoning core for image generation, decoupling a Thinker from the generator. It uses reinforcement learning to optimize visual correctness, substantially improving image reasoning and generation quality.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03127
• PDF: https://arxiv.org/pdf/2601.03127

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

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#ImageGeneration #AIResearch #ReinforcementLearning #DeepLearning #GenerativeAI

✨Large Reasoning Models Are (Not Yet) Multilingual Latent Reasoners

📝 Summary:
Large reasoning models show multilingual latent reasoning, stronger in resource-rich languages but weaker in low-resource ones. Despite varying strength, their internal prediction evolution is consistent across languages, suggesting an English-centered latent reasoning pathway.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02996
• PDF: https://arxiv.org/pdf/2601.02996
• Github: https://github.com/cisnlp/multilingual-latent-reasoner

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✨UniVideo: Unified Understanding, Generation, and Editing for Videos

📝 Summary:
UniVideo, a dual-stream framework combining a Multimodal Large Language Model and a Multimodal DiT, extends unified modeling to video generation and editing, achieving state-of-the-art performance and...

🔹 Publication Date: Published on Oct 9, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.08377
• PDF: https://arxiv.org/pdf/2510.08377
• Project Page: https://congwei1230.github.io/UniVideo/
• Github: https://github.com/KwaiVGI/UniVideo

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

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✨MindWatcher: Toward Smarter Multimodal Tool-Integrated Reasoning

📝 Summary:
MindWatcher is a tool-integrated reasoning agent using interleaved thinking and multimodal chain-of-thought. It autonomously coordinates diverse tools for complex tasks without human prompts. It outperforms larger models and provides agent training insights.

🔹 Publication Date: Published on Dec 29, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.23412
• PDF: https://arxiv.org/pdf/2512.23412
• Github: https://github.com/TIMMY-CHAN/MindWatcher

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✨MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamics

📝 Summary:
MDAgent2 enables automated molecular dynamics code generation and question answering through domain-adapted language models and a multi-agent runtime system. AI-generated summary Molecular dynamics (M...

🔹 Publication Date: Published on Jan 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02075
• PDF: https://arxiv.org/pdf/2601.02075
• Github: https://github.com/FredericVAN/PKU_MDAgent2

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✨Choreographing a World of Dynamic Objects

📝 Summary:
CHORD is a universal generative framework that extracts Lagrangian motion information from Eulerian video representations to synthesize diverse 4D dynamic scenes without requiring category-specific ru...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04194
• PDF: https://arxiv.org/pdf/2601.04194
• Project Page: https://yanzhelyu.github.io/chord/

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✨EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering for Enhanced Alignment and Reasoning

📝 Summary:
EpiQAL presents a novel benchmark for evaluating epidemiological reasoning in language models through three distinct subsets measuring factual recall, multi-step inference, and conclusion reconstructi...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03471
• PDF: https://arxiv.org/pdf/2601.03471

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✨E-GRPO: High Entropy Steps Drive Effective Reinforcement Learning for Flow Models

📝 Summary:
Entropy-aware policy optimization method for reinforcement learning in flow matching models that improves exploration through SDE and ODE sampling strategies. AI-generated summary Recent reinforcement...

🔹 Publication Date: Published on Jan 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.00423
• PDF: https://arxiv.org/pdf/2601.00423
• Github: https://github.com/shengjun-zhang/VisualGRPO

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