✨MAGMA: A Multi-Graph based Agentic Memory Architecture for AI Agents

📝 Summary:
MAGMA is a multi-graph memory architecture that improves AI agent long-context reasoning. It decouples memory representation from retrieval logic across semantic, temporal, causal, and entity graphs for query-adaptive selection, outperforming existing agentic memory systems.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03236
• PDF: https://arxiv.org/pdf/2601.03236

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#AIAgents #MemoryArchitecture #LongContextReasoning #GraphAI #ArtificialIntelligence

✨SimpleMem: Efficient Lifelong Memory for LLM Agents

📝 Summary:
SimpleMem is an efficient memory framework for LLM agents that uses semantic lossless compression. It employs a three-stage pipeline to distill, consolidate, and retrieve historical experiences efficiently. SimpleMem significantly improves accuracy and reduces token consumption by up to 30-fold c...

🔹 Publication Date: Published on Jan 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02553
• PDF: https://arxiv.org/pdf/2601.02553
• Project Page: https://aiming-lab.github.io/SimpleMem-Page/
• Github: https://aiming-lab.github.io/SimpleMem-Page/

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#LLM #AIAgents #LifelongLearning #AI #DeepLearning

✨RGS-SLAM: Robust Gaussian Splatting SLAM with One-Shot Dense Initialization

📝 Summary:
RGS-SLAM is a robust Gaussian-splatting SLAM framework that uses a one-shot, correspondence-to-Gaussian initialization with DINOv3 descriptors. This method improves stability, accelerates convergence, and yields higher rendering fidelity and accuracy compared to existing systems.

🔹 Publication Date: Published on Dec 28, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.00705
• PDF: https://arxiv.org/pdf/2601.00705

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#SLAM #GaussianSplatting #ComputerVision #Robotics #DeepLearning

✨Enhancing Linguistic Competence of Language Models through Pre-training with Language Learning Tasks

📝 Summary:
L2T, a new pre-training framework, integrates language learning tasks with next-token prediction. This enhances language models' linguistic competence and acquisition without sacrificing general reasoning.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03448
• PDF: https://arxiv.org/pdf/2601.03448
• Project Page: https://huggingface.co/l2t-project/l2t-500m-disjoint-mix_75
• Github: https://github.com/gucci-j/l2t

🔹 Models citing this paper:
• https://huggingface.co/l2t-project/l2t-500m-disjoint
• https://huggingface.co/l2t-project/l2t-500m-disjoint-mix_0
• https://huggingface.co/l2t-project/l2t-500m-disjoint-mix_25

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#LLM #NLP #Pretraining #LanguageLearning #AI

✨Why LLMs Aren't Scientists Yet: Lessons from Four Autonomous Research Attempts

📝 Summary:
A case study of four LLM agent attempts to autonomously generate ML research papers reveals six recurring failure modes. Most attempts failed, though one was accepted to a special AI-first author venue, leading to proposed design principles for future AI-scientist systems.

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03315
• PDF: https://arxiv.org/pdf/2601.03315

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#LLMs #AIResearch #MachineLearning #AIAgents #AutonomousSystems

✨Gen3R: 3D Scene Generation Meets Feed-Forward Reconstruction

📝 Summary:
Gen3R combines reconstruction and video diffusion models to generate 3D scenes. It produces RGB videos and 3D geometry by aligning geometric and appearance latents. This achieves state-of-the-art results and improves reconstruction robustness.

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04090
• PDF: https://arxiv.org/pdf/2601.04090
• Project Page: https://xdimlab.github.io/Gen3R/
• Github: https://xdimlab.github.io/Gen3R/

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#3DGeneration #DiffusionModels #ComputerVision #3DReconstruction #DeepLearning

✨Evolving Programmatic Skill Networks

📝 Summary:
The Programmatic Skill Network PSN enables continual skill acquisition through executable symbolic programs that evolve via reflection, progressive optimization, and structural refactoring. This framework demonstrates robust skill reuse, rapid adaptation, and strong generalization in open-ended e...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03509
• PDF: https://arxiv.org/pdf/2601.03509

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#ProgrammaticAI #SkillAcquisition #EvolutionaryAI #MachineLearning #AIResearch

✨Pearmut: Human Evaluation of Translation Made Trivial

📝 Summary:
Pearmut is a lightweight platform that simplifies complex human evaluation for multilingual NLP, particularly machine translation. It removes setup barriers by supporting various protocols, document context, and learning strategies. This makes reliable human evaluation a routine and practical par...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02933
• PDF: https://arxiv.org/pdf/2601.02933
• Github: https://github.com/zouharvi/pearmut

✨ Datasets citing this paper:
• https://huggingface.co/datasets/zouharvi/hearing2translate-humeval

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨ResTok: Learning Hierarchical Residuals in 1D Visual Tokenizers for Autoregressive Image Generation

📝 Summary:
A novel 1D visual tokenizer called Residual Tokenizer is introduced that incorporates hierarchical residuals to improve autoregressive image generation by leveraging vision-specific design principles ...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03955
• PDF: https://arxiv.org/pdf/2601.03955

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨ROI-Reasoning: Rational Optimization for Inference via Pre-Computation Meta-Cognition

📝 Summary:
ROI Reasoning enables large language models to strategically allocate computation under strict token budgets. It uses meta-cognition to predict costs and utilities, optimizing sequential decisions with reinforcement learning. This improves performance and reduces regret on budgeted reasoning tasks.

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03822
• PDF: https://arxiv.org/pdf/2601.03822

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨RelayLLM: Efficient Reasoning via Collaborative Decoding

📝 Summary:
RelayLLM enables efficient collaborative reasoning by having a small language model dynamically invoke a large language model only for critical tokens. This token-level collaboration achieves high accuracy with minimal computational overhead. It reduces LLM invocation to just 1.07% of tokens, lea...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05167
• PDF: https://arxiv.org/pdf/2601.05167

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨VideoAuto-R1: Video Auto Reasoning via Thinking Once, Answering Twice

📝 Summary:
VideoAuto-R1 framework employs a reason-when-necessary strategy for video understanding, using a Thinking Once, Answering Twice training paradigm with verifiable rewards and confidence-based reasoning...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05175
• PDF: https://arxiv.org/pdf/2601.05175
• Project Page: https://ivul-kaust.github.io/projects/videoauto-r1/

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨VerseCrafter: Dynamic Realistic Video World Model with 4D Geometric Control

📝 Summary:
VerseCrafter is a 4D-aware video world model that enables unified control over camera and object dynamics through 4D geometric control representation and video diffusion models. AI-generated summary V...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05138
• PDF: https://arxiv.org/pdf/2601.05138

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Agent-as-a-Judge

📝 Summary:
Large language models face limitations in evaluating complex, multi-step tasks, prompting the development of agent-based evaluation systems that utilize planning, tool-augmented verification, and mult...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05111
• PDF: https://arxiv.org/pdf/2601.05111

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨DiffCoT: Diffusion-styled Chain-of-Thought Reasoning in LLMs

📝 Summary:
DiffCoT reformulates chain-of-thought reasoning as an iterative denoising process using diffusion principles, enabling unified generation and correction of intermediate steps while maintaining causal ...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03559
• PDF: https://arxiv.org/pdf/2601.03559

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨The Illusion of Specialization: Unveiling the Domain-Invariant "Standing Committee" in Mixture-of-Experts Models

📝 Summary:
Research challenges the assumption of domain specialization in Mixture of Experts models by identifying a persistent central committee of experts that dominates routing behavior across different domai...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03425
• PDF: https://arxiv.org/pdf/2601.03425

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization

📝 Summary:
Multi-reward RL with GRPO suffers from reward normalization collapse, leading to suboptimal training. GDPO solves this by decoupling individual reward normalization, preserving their relative differences for improved stability and optimization. GDPO consistently outperforms GRPO across various re...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05242
• PDF: https://arxiv.org/pdf/2601.05242
• Project Page: https://nvlabs.github.io/GDPO/
• Github: https://github.com/NVlabs/GDPO

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Plenoptic Video Generation

📝 Summary:
PlenopticDreamer enables consistent multi-view video re-rendering through synchronized generative hallucinations, leveraging camera-guided retrieval and progressive training mechanisms for improved te...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05239
• PDF: https://arxiv.org/pdf/2601.05239
• Project Page: https://research.nvidia.com/labs/dir/plenopticdreamer/

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨DocDancer: Towards Agentic Document-Grounded Information Seeking

📝 Summary:
DocDancer is an end-to-end trained open-source document question answering agent that formulates the task as an information-seeking problem and uses a tool-driven framework with exploration and synthe...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05163
• PDF: https://arxiv.org/pdf/2601.05163

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Token-Level LLM Collaboration via FusionRoute

📝 Summary:
FusionRoute is a token-level multi-LLM collaboration framework that uses a lightweight router to select optimal experts and add complementary logits, outperforming existing methods in diverse tasks wh...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05106
• PDF: https://arxiv.org/pdf/2601.05106

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

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#AI #DataScience #MachineLearning #HuggingFace #Research