✨A Pragmatic VLA Foundation Model

📝 Summary:
A Vision-Language-Action model trained on extensive real-world robotic data demonstrates superior performance and generalization across multiple platforms while offering enhanced efficiency through op...

🔹 Publication Date: Published on Jan 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.18692
• PDF: https://arxiv.org/pdf/2601.18692
• Project Page: https://technology.robbyant.com/lingbot-vla
• Github: https://github.com/robbyant/lingbot-vla

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨FastNeRF: High-Fidelity Neural Rendering at 200FPS

📝 Summary:
FastNeRF enables high-speed rendering of photorealistic 3D environments by factorizing radiance maps for efficient pixel value estimation. AI-generated summary Recent work on Neural Radiance Fields ( ...

🔹 Publication Date: Published on Mar 18, 2021

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2103.10380
• PDF: https://arxiv.org/pdf/2103.10380
• Github: https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/FastNeRF_High_Fidelity_Neural_Rendering_at_200FPS

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨World Craft: Agentic Framework to Create Visualizable Worlds via Text

📝 Summary:
World Craft enables non-expert users to create executable and visualizable AI environments through textual descriptions by combining structured scaffolding and multi-agent intent analysis. AI-generate...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09150
• PDF: https://arxiv.org/pdf/2601.09150
• Github: https://github.com/HerzogFL/World-Craft

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨TriPlay-RL: Tri-Role Self-Play Reinforcement Learning for LLM Safety Alignment

📝 Summary:
TriPlay-RL is a closed-loop reinforcement learning framework for LLM safety alignment. It iteratively improves attacker, defender, and evaluator roles with near-zero manual annotation. This leads to better adversarial effectiveness, enhanced safety performance, and refined judgment.

🔹 Publication Date: Published on Jan 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.18292
• PDF: https://arxiv.org/pdf/2601.18292

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

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#LLM #ReinforcementLearning #AISafety #MachineLearning #SelfPlay

✨FABLE: Forest-Based Adaptive Bi-Path LLM-Enhanced Retrieval for Multi-Document Reasoning

📝 Summary:
FABLE is a new retrieval framework enhancing LLM-based multi-document reasoning through hierarchical forest indexes and a bi-path strategy. It outperforms traditional RAG with up to 94 percent token reduction, proving the ongoing need for structured retrieval.

🔹 Publication Date: Published on Jan 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.18116
• PDF: https://arxiv.org/pdf/2601.18116

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

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#LLM #InformationRetrieval #MultiDocumentReasoning #RAG #NLP

✨HalluCitation Matters: Revealing the Impact of Hallucinated References with 300 Hallucinated Papers in ACL Conferences

📝 Summary:
Hallucinated citations HalluCitation are a growing problem in NLP papers. This study found nearly 300 papers from 2024-2025 contain HalluCitations, with a rapid increase at EMNLP 2025, threatening scientific reliability and conference credibility.

🔹 Publication Date: Published on Jan 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.18724
• PDF: https://arxiv.org/pdf/2601.18724

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

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#HalluCitation #NLP #ResearchIntegrity #AI #AcademicPublishing

✨Benchmarks Saturate When The Model Gets Smarter Than The Judge

📝 Summary:
This paper introduces Omni-MATH-2, a manually audited mathematical benchmark dataset to reduce noise. It reveals that existing judges like Omni-Judge are highly inaccurate, masking real model performance differences. Accurate benchmarks require both high-quality datasets and more competent judges.

🔹 Publication Date: Published on Jan 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.19532
• PDF: https://arxiv.org/pdf/2601.19532

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

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#AI #MachineLearning #Benchmarking #ModelEvaluation #Datasets

✨Post-LayerNorm Is Back: Stable, ExpressivE, and Deep

📝 Summary:
Keel is a novel Post-LayerNorm Transformer using Highway-style connections instead of residual ones. This enables stable training of networks over 1000 layers deep, preventing gradient vanishing and improving expressivity for LLMs.

🔹 Publication Date: Published on Jan 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.19895
• PDF: https://arxiv.org/pdf/2601.19895

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

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#Transformers #DeepLearning #LLM #NeuralNetworks #AIResearch

✨EvolVE: Evolutionary Search for LLM-based Verilog Generation and Optimization

📝 Summary:
EvolVE improves LLM-based Verilog generation and optimization through evolutionary search. It uses MCTS for correctness and IGR for optimization, accelerated by STG. EvolVE achieves state-of-the-art performance and reduces PPA on industry-scale designs.

🔹 Publication Date: Published on Jan 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.18067
• PDF: https://arxiv.org/pdf/2601.18067
• Github: https://github.com/weiber2002/ICRTL

✨ Datasets citing this paper:
• https://huggingface.co/datasets/weiber2002/ICRTL

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

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#LLM #Verilog #EvolutionaryAlgorithms #HardwareDesign #AI

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✨DeFM: Learning Foundation Representations from Depth for Robotics

📝 Summary:
DeFM is a self-supervised foundation model for depth representation learning in robotics. It learns geometric and semantic features from 60M depth images, achieving state-of-the-art performance across diverse robotic tasks and strong sim-to-real generalization.

🔹 Publication Date: Published on Jan 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.18923
• PDF: https://arxiv.org/pdf/2601.18923
• Github: https://de-fm.github.io/

🔹 Models citing this paper:
• https://huggingface.co/leggedrobotics/defm

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

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#Robotics #FoundationModels #SelfSupervisedLearning #ComputerVision #MachineLearning

✨HyperAlign: Hypernetwork for Efficient Test-Time Alignment of Diffusion Models

📝 Summary:
HyperAlign uses a hypernetwork to efficiently align diffusion models at test-time. It dynamically adjusts denoising trajectories based on input conditions, improving semantic consistency and visual appeal. This outperforms existing methods.

🔹 Publication Date: Published on Jan 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.15968
• PDF: https://arxiv.org/pdf/2601.15968

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

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#DiffusionModels #Hypernetworks #GenerativeAI #AIResearch #DeepLearning

✨Towards Pixel-Level VLM Perception via Simple Points Prediction

📝 Summary:
SimpleSeg enables MLLMs to perform pixel-level segmentation by predicting point sequences in language space. A two-stage training with reinforcement learning refines these points. This simple method achieves competitive results, showing MLLMs have inherent low-level perception without specialized...

🔹 Publication Date: Published on Jan 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.19228
• PDF: https://arxiv.org/pdf/2601.19228
• Project Page: https://simpleseg.github.io/
• Github: https://github.com/songtianhui/SimpleSeg

🔹 Models citing this paper:
• https://huggingface.co/sthui/SimpleSeg-Kimi-VL
• https://huggingface.co/sthui/SimpleSeg-Qwen2.5-VL

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

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#VLM #MLLM #ImageSegmentation #DeepLearning #AIResearch

✨Youtu-VL: Unleashing Visual Potential via Unified Vision-Language Supervision

📝 Summary:
Youtu-VL introduces a Vision-Language Unified Autoregressive Supervision paradigm. It shifts from vision-as-input to vision-as-target, integrating visual tokens into the prediction stream. This improves multimodal comprehension and vision-centric task performance, fostering generalist visual agents.

🔹 Publication Date: Published on Jan 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.19798
• PDF: https://arxiv.org/pdf/2601.19798
• Project Page: https://youtu-tip.com/#llm
• Github: https://github.com/TencentCloudADP/youtu-vl

🔹 Models citing this paper:
• https://huggingface.co/tencent/Youtu-VL-4B-Instruct
• https://huggingface.co/tencent/Youtu-VL-4B-Instruct-GGUF
• https://huggingface.co/tencent/Youtu-Parsing

✨ Spaces citing this paper:
• https://huggingface.co/spaces/tencent/Youtu-Parsing

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

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#YoutuVL #VisionLanguage #MultimodalAI #ComputerVision #DeepLearning

✨CooperBench: Why Coding Agents Cannot be Your Teammates Yet

📝 Summary:
AI agents lack social intelligence for teamwork. CooperBench, a new collaborative coding benchmark, shows agents perform 30% worse together than individually. This 'curse of coordination' is due to poor communication, broken commitments, and incorrect expectations, calling for AI to develop socia...

🔹 Publication Date: Published on Jan 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.13295
• PDF: https://arxiv.org/pdf/2601.13295
• Project Page: https://cooperbench.com
• Github: https://github.com/cooperbench/CooperBench

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Self-Distillation Enables Continual Learning

📝 Summary:
Self-Distillation Fine-Tuning enables on-policy continual learning from demonstrations. It uses the model as its own teacher to acquire new skills while preserving prior knowledge. This method significantly reduces catastrophic forgetting and allows models to accumulate multiple skills over time.

🔹 Publication Date: Published on Jan 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.19897
• PDF: https://arxiv.org/pdf/2601.19897

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨GDCNet: Generative Discrepancy Comparison Network for Multimodal Sarcasm Detection

📝 Summary:
A multimodal sarcasm detection approach uses generative models to create stable semantic anchors and measures cross-modal discrepancies for improved accuracy and robustness. AI-generated summary Multi...

🔹 Publication Date: Published on Jan 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.20618
• PDF: https://arxiv.org/pdf/2601.20618

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Harder Is Better: Boosting Mathematical Reasoning via Difficulty-Aware GRPO and Multi-Aspect Question Reformulation

📝 Summary:
MathForge enhances mathematical reasoning in large models through a dual framework combining difficulty-aware policy optimization and multi-aspect question reformulation to address limitations in exis...

🔹 Publication Date: Published on Jan 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.20614
• PDF: https://arxiv.org/pdf/2601.20614
• Github: https://github.com/AMAP-ML/MathForge

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨RIR-Mega-Speech: A Reverberant Speech Corpus with Comprehensive Acoustic Metadata and Reproducible Evaluation

📝 Summary:
A large-scale reverberant speech corpus with detailed acoustic annotations is introduced to facilitate standardized comparison and reproduction of speech processing research. AI-generated summary Desp...

🔹 Publication Date: Published on Jan 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.19949
• PDF: https://arxiv.org/pdf/2601.19949
• Project Page: https://huggingface.co/datasets/mandipgoswami/rir-mega-speech

✨ Datasets citing this paper:
• https://huggingface.co/datasets/mandipgoswami/rirmega
• https://huggingface.co/datasets/mandipgoswami/rir-mega-speech

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Advancing Open-source World Models

📝 Summary:
LingBot-World is an open-source world simulator offering high-fidelity dynamics in diverse environments. It features long-term memory and real-time interactivity. This release empowers the community for applications like content creation, gaming, and robot learning.

🔹 Publication Date: Published on Jan 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.20540
• PDF: https://arxiv.org/pdf/2601.20540
• Project Page: https://technology.robbyant.com/lingbot-world
• Github: https://github.com/Robbyant/lingbot-world/

🔹 Models citing this paper:
• https://huggingface.co/robbyant/lingbot-world-base-cam

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

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#AI #DataScience #MachineLearning #HuggingFace #Research