✨ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios

📝 Summary:
ViDoRe v3 is a new multimodal RAG benchmark for complex queries over visually rich, multi-language documents. It shows visual retrievers and late-interaction models improve performance, though models struggle with non-textual elements and visual grounding.

🔹 Publication Date: Published on Jan 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.08620
• PDF: https://arxiv.org/pdf/2601.08620

✨ Datasets citing this paper:
• https://huggingface.co/datasets/vidore/vidore_v3_physics
• https://huggingface.co/datasets/vidore/vidore_v3_computer_science
• https://huggingface.co/datasets/vidore/vidore_v3_finance_en

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

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#RAG #MultimodalAI #AIResearch #NLP #ComputerVision

✨VideoLoom: A Video Large Language Model for Joint Spatial-Temporal Understanding

📝 Summary:
VideoLoom is a unified video large language model that achieves state-of-the-art performance in spatial-temporal video understanding through a specialized dataset and benchmark. AI-generated summary T...

🔹 Publication Date: Published on Jan 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07290
• PDF: https://arxiv.org/pdf/2601.07290
• Github: https://github.com/JPShi12/VideoLoom

🔹 Models citing this paper:
• https://huggingface.co/JPShi/VideoLoom-4B
• https://huggingface.co/JPShi/VideoLoom-8B

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

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✨UM-Text: A Unified Multimodal Model for Image Understanding

📝 Summary:
A unified multimodal model for visual text editing that understands natural language instructions and maintains stylistic consistency with reference images through visual language modeling and context...

🔹 Publication Date: Published on Jan 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.08321
• PDF: https://arxiv.org/pdf/2601.08321

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

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✨GeoMotionGPT: Geometry-Aligned Motion Understanding with Large Language Models

📝 Summary:
GeoMotionGPT introduces a framework aligning motion token geometry with language model embeddings using orthogonal constraints and sparse projection. This unified geometric basis enhances LLM motion reasoning, achieving a 20% performance improvement on HumanML3D.

🔹 Publication Date: Published on Jan 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07632
• PDF: https://arxiv.org/pdf/2601.07632
• Project Page: https://huggingface.co/papers?q=sparse%20projection
• Github: https://github.com/JYe16/GeoMotionGPT

🔹 Models citing this paper:
• https://huggingface.co/zy22b/GeoMotionGPT

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

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✨The Agent's First Day: Benchmarking Learning, Exploration, and Scheduling in the Workplace Scenarios

📝 Summary:
EvoEnv is a new dynamic evaluation environment for MLLMs. It assesses agent robustness in real-world tasks, focusing on context-aware scheduling, active exploration, and continuous learning. Current MLLMs show significant deficiencies in these dynamic scenarios.

🔹 Publication Date: Published on Jan 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.08173
• PDF: https://arxiv.org/pdf/2601.08173
• Github: https://github.com/KnowledgeXLab/EvoEnv

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

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✨Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning

📝 Summary:
Fast-ThinkAct is an efficient vision-language-action framework that reduces inference latency by 89.3% through compact latent reasoning while maintaining long-horizon planning and few-shot adaptation ...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09708
• PDF: https://arxiv.org/pdf/2601.09708
• Project Page: https://jasper0314-huang.github.io/fast-thinkact/
• Github: https://jasper0314-huang.github.io/fast-thinkact/

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

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✨A^3-Bench: Benchmarking Memory-Driven Scientific Reasoning via Anchor and Attractor Activation

📝 Summary:
Scientific reasoning relies not only on logical inference but also on activating prior knowledge and experiential structures. Memory can efficiently reuse knowledge and enhance reasoning consistency a...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09274
• PDF: https://arxiv.org/pdf/2601.09274

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

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✨MAXS: Meta-Adaptive Exploration with LLM Agents

📝 Summary:
MAXS is a meta-adaptive reasoning framework for LLM agents that improves multi-tool reasoning through lookahead strategies and trajectory convergence mechanisms, balancing global effectiveness and com...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09259
• PDF: https://arxiv.org/pdf/2601.09259

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

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✨Controlled Self-Evolution for Algorithmic Code Optimization

📝 Summary:
Controlled Self-Evolution method improves code generation through diversified initialization, feedback-guided genetic evolution, and hierarchical memory to enhance exploration efficiency and solution ...

🔹 Publication Date: Published on Jan 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07348
• PDF: https://arxiv.org/pdf/2601.07348

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

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✨SkinFlow: Efficient Information Transmission for Open Dermatological Diagnosis via Dynamic Visual Encoding and Staged RL

📝 Summary:
SkinFlow optimizes dermatological diagnosis by enhancing visual information transmission efficiency, addressing 'diffuse attention' in large models. It uses a Dynamic Vision Encoder and two-stage RL to significantly outperform massive general-purpose models, proving efficiency beats raw parameter...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09136
• PDF: https://arxiv.org/pdf/2601.09136

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

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✨Are LLMs Vulnerable to Preference-Undermining Attacks (PUA)? A Factorial Analysis Methodology for Diagnosing the Trade-off between Preference Alignment and Real-World Validity

📝 Summary:
Research examines how large language models can be manipulated through preference-undermining attacks that exploit alignment objectives, revealing model vulnerabilities and proposing a factorial evalu...

🔹 Publication Date: Published on Jan 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.06596
• PDF: https://arxiv.org/pdf/2601.06596

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

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✨FocusUI: Efficient UI Grounding via Position-Preserving Visual Token Selection

📝 Summary:
FocusUI is an efficient UI grounding framework that reduces computational overhead by selecting relevant visual tokens while preserving positional continuity through a novel PosPad strategy. AI-genera...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2601.03928
• PDF: https://arxiv.org/pdf/2601.03928
• Github: https://github.com/showlab/FocusUI

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

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✨Efficient Camera-Controlled Video Generation of Static Scenes via Sparse Diffusion and 3D Rendering

📝 Summary:
Diffusion-based video generation is made more efficient through keyframe-based 3D reconstruction and rendering, enabling faster synthesis with maintained visual quality. AI-generated summary Modern vi...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09697
• PDF: https://arxiv.org/pdf/2601.09697

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

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✨DeepResearchEval: An Automated Framework for Deep Research Task Construction and Agentic Evaluation

📝 Summary:
DeepResearchEval presents an automated framework for creating complex research tasks and evaluating them through agent-based methods that adapt to task specifics and verify facts without relying on ci...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09688
• PDF: https://arxiv.org/pdf/2601.09688
• Github: https://github.com/Infinity-AILab/DeepResearchEval

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

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✨TranslateGemma Technical Report

📝 Summary:
TranslateGemma enhances Gemma 3's multilingual capabilities through two-stage fine-tuning with synthetic and human-translated data, achieving superior translation quality with improved efficiency. AI-...

🔹 Publication Date: Published on Jan 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09012
• PDF: https://arxiv.org/pdf/2601.09012

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

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✨OpenVoxel: Training-Free Grouping and Captioning Voxels for Open-Vocabulary 3D Scene Understanding

📝 Summary:
OpenVoxel enables open-vocabulary 3D scene understanding through training-free grouping and captioning of sparse voxels using Vision Language Models and Multi-modal Large Language Models. AI-generated...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09575
• PDF: https://arxiv.org/pdf/2601.09575

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

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✨EvoFSM: Controllable Self-Evolution for Deep Research with Finite State Machines

📝 Summary:
EvoFSM is a structured self-evolving framework for LLM agents that uses finite state machines to improve adaptability while maintaining control through constrained optimization and memory mechanisms. ...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09465
• PDF: https://arxiv.org/pdf/2601.09465

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

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✨The AI Hippocampus: How Far are We From Human Memory?

📝 Summary:
Memory mechanisms in large language models and multi-modal language models are categorized into implicit, explicit, and agentic paradigms, supporting enhanced reasoning, adaptability, and contextual f...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09113
• PDF: https://arxiv.org/pdf/2601.09113

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

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✨ExpSeek: Self-Triggered Experience Seeking for Web Agents

📝 Summary:
ExpSeek enables web agents to proactively seek experience during interaction using entropy-based timing and tailored content. This step-level approach significantly improves performance over passive methods, even when using smaller experience models.

🔹 Publication Date: Published on Jan 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.08605
• PDF: https://arxiv.org/pdf/2601.08605

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

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✨Imagine-then-Plan: Agent Learning from Adaptive Lookahead with World Models

📝 Summary:
Imagine-then-Plan framework enables agent learning through adaptive lookahead imagination, combining imagined trajectories with current observations to guide policy learning in complex task scenarios....

🔹 Publication Date: Published on Jan 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.08955
• PDF: https://arxiv.org/pdf/2601.08955

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

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