✨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
📝 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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❤1
✨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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📝 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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✨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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📝 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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❤1
✨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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📝 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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✨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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📝 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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✨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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📝 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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✨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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📝 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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✨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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📝 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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✨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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📝 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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✨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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📝 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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