✨Toward Stable Semi-Supervised Remote Sensing Segmentation via Co-Guidance and Co-Fusion

📝 Summary:
A semi-supervised remote sensing image segmentation framework combines vision-language and self-supervised models to reduce pseudo-label drift through dual-student architecture and semantic co-guidanc...

🔹 Publication Date: Published on Dec 28, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.23035
• PDF: https://arxiv.org/pdf/2512.23035
• Project Page: https://xavierjiezou.github.io/Co2S/
• Github: https://github.com/XavierJiezou/Co2S

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving

📝 Summary:
SWE-Lego achieves state-of-the-art software issue resolution through a lightweight supervised fine-tuning approach. It uses a high-quality dataset and refined training procedures like error masking and a difficulty-based curriculum, outperforming complex methods. Performance is further boosted by...

🔹 Publication Date: Published on Jan 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01426
• PDF: https://arxiv.org/pdf/2601.01426
• Project Page: https://github.com/SWE-Lego/SWE-Lego
• Github: https://github.com/SWE-Lego/SWE-Lego

🔹 Models citing this paper:
• https://huggingface.co/SWE-Lego/SWE-Lego-Qwen3-8B
• https://huggingface.co/SWE-Lego/SWE-Lego-Qwen3-32B

✨ Datasets citing this paper:
• https://huggingface.co/datasets/SWE-Lego/SWE-Lego-Real-Data
• https://huggingface.co/datasets/SWE-Lego/SWE-Lego-Synthetic-Data

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#SoftwareEngineering #MachineLearning #LLM #FineTuning #AIforCode

✨M-ErasureBench: A Comprehensive Multimodal Evaluation Benchmark for Concept Erasure in Diffusion Models

📝 Summary:
Existing concept erasure methods in diffusion models are vulnerable to non-text inputs. M-ErasureBench is a new multimodal evaluation framework, and IRECE is a module to restore robustness against these attacks, reducing concept reproduction.

🔹 Publication Date: Published on Dec 28, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.22877
• PDF: https://arxiv.org/pdf/2512.22877

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#DiffusionModels #ConceptErasure #MultimodalAI #AISafety #MachineLearning

✨InfiniDepth: Arbitrary-Resolution and Fine-Grained Depth Estimation with Neural Implicit Fields

📝 Summary:
InfiniDepth represents depth as neural implicit fields using a local implicit decoder, enabling continuous 2D coordinate querying for arbitrary-resolution depth estimation and superior performance in ...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03252
• PDF: https://arxiv.org/pdf/2601.03252
• Github: https://zju3dv.github.io/InfiniDepth

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨FFP-300K: Scaling First-Frame Propagation for Generalizable Video Editing

📝 Summary:
A new large-scale video dataset and framework are presented that enable effective first-frame propagation without runtime guidance through adaptive spatio-temporal positional encoding and self-distill...

🔹 Publication Date: Published on Jan 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01720
• PDF: https://arxiv.org/pdf/2601.01720
• Project Page: https://ffp-300k.github.io/

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✨MOSS Transcribe Diarize: Accurate Transcription with Speaker Diarization

📝 Summary:
A unified multimodal large language model for end-to-end speaker-attributed, time-stamped transcription with extended context window and strong generalization across benchmarks. AI-generated summary S...

🔹 Publication Date: Published on Jan 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01554
• PDF: https://arxiv.org/pdf/2601.01554
• Project Page: https://mosi.cn/models/moss-transcribe-diarize

✨ Spaces citing this paper:
• https://huggingface.co/spaces/OpenMOSS-Team/MOSS-transcribe-diarize

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨CogFlow: Bridging Perception and Reasoning through Knowledge Internalization for Visual Mathematical Problem Solving

📝 Summary:
Visual mathematical problem solving remains challenging for multimodal large language models, prompting the development of CogFlow, a cognitive-inspired three-stage framework that enhances perception,...

🔹 Publication Date: Published on Jan 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.01874
• PDF: https://arxiv.org/pdf/2601.01874
• Project Page: https://shchen233.github.io/cogflow/
• Github: https://shchen233.github.io/cogflow/

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✨NitroGen: An Open Foundation Model for Generalist Gaming Agents

📝 Summary:
NitroGen is a vision-action foundation model trained on extensive gameplay data that demonstrates strong cross-game generalization and effective transfer learning capabilities. AI-generated summary We...

🔹 Publication Date: Published on Jan 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.02427
• PDF: https://arxiv.org/pdf/2601.02427
• Project Page: https://nitrogen.minedojo.org/
• Github: https://github.com/MineDojo/NitroGen

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨X-MuTeST: A Multilingual Benchmark for Explainable Hate Speech Detection and A Novel LLM-consulted Explanation Framework

📝 Summary:
A novel explainability-guided training framework for hate speech detection in Indic languages that combines large language models with attention-enhancing techniques and provides human-annotated ratio...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03194
• PDF: https://arxiv.org/pdf/2601.03194
• Github: https://github.com/ziarehman30/X-MuTeST

✨ Datasets citing this paper:
• https://huggingface.co/datasets/UVSKKR/X-MuTeST

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

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Parallel Latent Reasoning for Sequential Recommendation

📝 Summary:
Parallel Latent Reasoning framework improves sequential recommendation by exploring multiple diverse reasoning trajectories simultaneously through learnable trigger tokens and adaptive aggregation. AI...

🔹 Publication Date: Published on Jan 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.03153
• PDF: https://arxiv.org/pdf/2601.03153

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

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#AI #DataScience #MachineLearning #HuggingFace #Research