✨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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📝 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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📝 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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📝 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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📝 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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📝 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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📝 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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📝 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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📝 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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📝 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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📝 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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📝 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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📝 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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✨Focal Guidance: Unlocking Controllability from Semantic-Weak Layers in Video Diffusion Models
📝 Summary:
Diffusion Transformer-based image-to-video models suffer from condition isolation where visual attention becomes detached from text guidance; focal guidance addresses this through fine-grained semanti...
🔹 Publication Date: Published on Jan 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07287
• PDF: https://arxiv.org/pdf/2601.07287
==================================
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📝 Summary:
Diffusion Transformer-based image-to-video models suffer from condition isolation where visual attention becomes detached from text guidance; focal guidance addresses this through fine-grained semanti...
🔹 Publication Date: Published on Jan 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07287
• PDF: https://arxiv.org/pdf/2601.07287
==================================
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✨Distribution-Aligned Sequence Distillation for Superior Long-CoT Reasoning
📝 Summary:
DASD-4B-Thinking is a new lightweight model achieving state-of-the-art reasoning by enhancing sequence-level distillation. It addresses limitations in current teacher-student knowledge transfer by better capturing the teachers full output distribution, using significantly fewer training samples.
🔹 Publication Date: Published on Jan 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09088
• PDF: https://arxiv.org/pdf/2601.09088
• Project Page: https://github.com/D2I-ai/dasd-thinking
• Github: https://github.com/D2I-ai/dasd-thinking
🔹 Models citing this paper:
• https://huggingface.co/Alibaba-Apsara/DASD-4B-Thinking
• https://huggingface.co/Alibaba-Apsara/DASD-30B-A3B-Thinking-Preview
✨ Datasets citing this paper:
• https://huggingface.co/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b
• https://huggingface.co/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob
==================================
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📝 Summary:
DASD-4B-Thinking is a new lightweight model achieving state-of-the-art reasoning by enhancing sequence-level distillation. It addresses limitations in current teacher-student knowledge transfer by better capturing the teachers full output distribution, using significantly fewer training samples.
🔹 Publication Date: Published on Jan 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09088
• PDF: https://arxiv.org/pdf/2601.09088
• Project Page: https://github.com/D2I-ai/dasd-thinking
• Github: https://github.com/D2I-ai/dasd-thinking
🔹 Models citing this paper:
• https://huggingface.co/Alibaba-Apsara/DASD-4B-Thinking
• https://huggingface.co/Alibaba-Apsara/DASD-30B-A3B-Thinking-Preview
✨ Datasets citing this paper:
• https://huggingface.co/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b
• https://huggingface.co/datasets/Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b-Logprob
==================================
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arXiv.org
Distribution-Aligned Sequence Distillation for Superior Long-CoT Reasoning
In this report, we introduce DASD-4B-Thinking, a lightweight yet highly capable, fully open-source reasoning model. It achieves SOTA performance among open-source models of comparable scale across...
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✨Geometric Stability: The Missing Axis of Representations
📝 Summary:
This paper introduces geometric stability, a new metric quantifying how reliably representational geometry holds under perturbation. It is distinct from similarity, offering complementary insights for safety monitoring, controllability, and model selection across diverse systems.
🔹 Publication Date: Published on Jan 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09173
• PDF: https://arxiv.org/pdf/2601.09173
• Github: https://github.com/prashantcraju/geometric-stability
🔹 Models citing this paper:
• https://huggingface.co/pcr2120/shesha-geometry
==================================
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📝 Summary:
This paper introduces geometric stability, a new metric quantifying how reliably representational geometry holds under perturbation. It is distinct from similarity, offering complementary insights for safety monitoring, controllability, and model selection across diverse systems.
🔹 Publication Date: Published on Jan 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09173
• PDF: https://arxiv.org/pdf/2601.09173
• Github: https://github.com/prashantcraju/geometric-stability
🔹 Models citing this paper:
• https://huggingface.co/pcr2120/shesha-geometry
==================================
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✨Omni-R1: Towards the Unified Generative Paradigm for Multimodal Reasoning
📝 Summary:
Omni-R1 proposes unified generative multimodal reasoning. It uses intermediate image generation to enable diverse skills across tasks. Omni-R1-Zero, needing no multimodal data, matches or exceeds its performance, showing a promising path.
🔹 Publication Date: Published on Jan 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09536
• PDF: https://arxiv.org/pdf/2601.09536
🔹 Models citing this paper:
• https://huggingface.co/ModalityDance/Omni-R1
• https://huggingface.co/ModalityDance/Omni-R1-Zero
✨ Datasets citing this paper:
• https://huggingface.co/datasets/ModalityDance/Omni-Bench
==================================
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📝 Summary:
Omni-R1 proposes unified generative multimodal reasoning. It uses intermediate image generation to enable diverse skills across tasks. Omni-R1-Zero, needing no multimodal data, matches or exceeds its performance, showing a promising path.
🔹 Publication Date: Published on Jan 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09536
• PDF: https://arxiv.org/pdf/2601.09536
🔹 Models citing this paper:
• https://huggingface.co/ModalityDance/Omni-R1
• https://huggingface.co/ModalityDance/Omni-R1-Zero
✨ Datasets citing this paper:
• https://huggingface.co/datasets/ModalityDance/Omni-Bench
==================================
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✨LoongFlow: Directed Evolutionary Search via a Cognitive Plan-Execute-Summarize Paradigm
📝 Summary:
LoongFlow is a self-evolving agent that integrates LLMs into a cognitive Plan-Execute-Summarize PES paradigm for directed evolutionary search. It prevents premature convergence by balancing exploration and exploitation with a hybrid memory system. LoongFlow achieves superior solutions 60% more ef...
🔹 Publication Date: Published on Dec 30, 2025
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.24077
• PDF: https://arxiv.org/pdf/2512.24077
• Project Page: https://github.com/baidu-baige/LoongFlow
• Github: https://github.com/baidu-baige/LoongFlow
==================================
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#EvolutionarySearch #LLMs #CognitiveAI #AIAgents #Optimization
📝 Summary:
LoongFlow is a self-evolving agent that integrates LLMs into a cognitive Plan-Execute-Summarize PES paradigm for directed evolutionary search. It prevents premature convergence by balancing exploration and exploitation with a hybrid memory system. LoongFlow achieves superior solutions 60% more ef...
🔹 Publication Date: Published on Dec 30, 2025
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.24077
• PDF: https://arxiv.org/pdf/2512.24077
• Project Page: https://github.com/baidu-baige/LoongFlow
• Github: https://github.com/baidu-baige/LoongFlow
==================================
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✨Cluster Workload Allocation: Semantic Soft Affinity Using Natural Language Processing
📝 Summary:
This paper introduces an LLM-based approach to interpret natural language hints for cluster workload allocation. It achieved over 95% accuracy and improved placement compared to traditional methods, simplifying workload orchestration.
🔹 Publication Date: Published on Jan 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09282
• PDF: https://arxiv.org/pdf/2601.09282
==================================
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#ClusterAllocation #NLP #LLMs #WorkloadOrchestration #AIResearch
📝 Summary:
This paper introduces an LLM-based approach to interpret natural language hints for cluster workload allocation. It achieved over 95% accuracy and improved placement compared to traditional methods, simplifying workload orchestration.
🔹 Publication Date: Published on Jan 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09282
• PDF: https://arxiv.org/pdf/2601.09282
==================================
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✨SampoNLP: A Self-Referential Toolkit for Morphological Analysis of Subword Tokenizers
📝 Summary:
SampoNLP is a new corpus-free toolkit for creating morphological lexicons for Uralic languages. It was used to systematically evaluate BPE tokenizers, identifying optimal vocabulary sizes and demonstrating BPE's limitations for these highly agglutinative languages.
🔹 Publication Date: Published on Jan 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04469
• PDF: https://arxiv.org/pdf/2601.04469
• Github: https://github.com/AragonerUA/SampoNLP
==================================
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#NLP #ComputationalLinguistics #Morphology #Tokenization #UralicLanguages
📝 Summary:
SampoNLP is a new corpus-free toolkit for creating morphological lexicons for Uralic languages. It was used to systematically evaluate BPE tokenizers, identifying optimal vocabulary sizes and demonstrating BPE's limitations for these highly agglutinative languages.
🔹 Publication Date: Published on Jan 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.04469
• PDF: https://arxiv.org/pdf/2601.04469
• Github: https://github.com/AragonerUA/SampoNLP
==================================
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