✨BabyVision: Visual Reasoning Beyond Language
📝 Summary:
Current multimodal large language models exhibit significant gaps in fundamental visual understanding compared to human children, as demonstrated by the BabyVision benchmark. AI-generated summary Whil...
🔹 Publication Date: Published on Jan 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.06521
• PDF: https://arxiv.org/pdf/2601.06521
==================================
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📝 Summary:
Current multimodal large language models exhibit significant gaps in fundamental visual understanding compared to human children, as demonstrated by the BabyVision benchmark. AI-generated summary Whil...
🔹 Publication Date: Published on Jan 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.06521
• PDF: https://arxiv.org/pdf/2601.06521
==================================
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✨3D CoCa v2: Contrastive Learners with Test-Time Search for Generalizable Spatial Intelligence
📝 Summary:
3D CoCa v2 enhances 3D captioning by combining contrastive vision-language learning with spatially-aware 3D scene encoding and test-time search for improved generalization across diverse environments....
🔹 Publication Date: Published on Jan 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.06496
• PDF: https://arxiv.org/pdf/2601.06496
• Github: https://github.com/AIGeeksGroup/3DCoCav2
==================================
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📝 Summary:
3D CoCa v2 enhances 3D captioning by combining contrastive vision-language learning with spatially-aware 3D scene encoding and test-time search for improved generalization across diverse environments....
🔹 Publication Date: Published on Jan 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.06496
• PDF: https://arxiv.org/pdf/2601.06496
• Github: https://github.com/AIGeeksGroup/3DCoCav2
==================================
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✨e5-omni: Explicit Cross-modal Alignment for Omni-modal Embeddings
📝 Summary:
Omni-modal embedding models face challenges with modality-dependent similarity scaling, ineffective in-batch negatives, and mismatched statistics across modalities, which are addressed through explici...
🔹 Publication Date: Published on Jan 7
🔹 Paper Links:
• arXiv Page: https://huggingface.co/collections/Haon-Chen/e5-omni
• PDF: https://arxiv.org/pdf/2601.03666
🔹 Models citing this paper:
• https://huggingface.co/Haon-Chen/e5-omni-3B
• https://huggingface.co/Haon-Chen/e5-omni-7B
==================================
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📝 Summary:
Omni-modal embedding models face challenges with modality-dependent similarity scaling, ineffective in-batch negatives, and mismatched statistics across modalities, which are addressed through explici...
🔹 Publication Date: Published on Jan 7
🔹 Paper Links:
• arXiv Page: https://huggingface.co/collections/Haon-Chen/e5-omni
• PDF: https://arxiv.org/pdf/2601.03666
🔹 Models citing this paper:
• https://huggingface.co/Haon-Chen/e5-omni-3B
• https://huggingface.co/Haon-Chen/e5-omni-7B
==================================
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✨MegaFlow: Large-Scale Distributed Orchestration System for the Agentic Era
📝 Summary:
MegaFlow is a distributed orchestration system for large-scale AI agent training and evaluation. It addresses the lack of open-source infrastructure by providing efficient scheduling, resource allocation, and task management through modular services. MegaFlow successfully handles tens of thousand...
🔹 Publication Date: Published on Jan 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07526
• PDF: https://arxiv.org/pdf/2601.07526
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📝 Summary:
MegaFlow is a distributed orchestration system for large-scale AI agent training and evaluation. It addresses the lack of open-source infrastructure by providing efficient scheduling, resource allocation, and task management through modular services. MegaFlow successfully handles tens of thousand...
🔹 Publication Date: Published on Jan 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07526
• PDF: https://arxiv.org/pdf/2601.07526
==================================
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✨Dr. Zero: Self-Evolving Search Agents without Training Data
📝 Summary:
A data-free self-evolution framework enables large language models to autonomously improve reasoning capabilities through iterative question generation and solving, achieving performance comparable to...
🔹 Publication Date: Published on Jan 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07055
• PDF: https://arxiv.org/pdf/2601.07055
• Github: https://github.com/facebookresearch/drzero
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📝 Summary:
A data-free self-evolution framework enables large language models to autonomously improve reasoning capabilities through iterative question generation and solving, achieving performance comparable to...
🔹 Publication Date: Published on Jan 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07055
• PDF: https://arxiv.org/pdf/2601.07055
• Github: https://github.com/facebookresearch/drzero
==================================
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✨GlimpRouter: Efficient Collaborative Inference by Glimpsing One Token of Thoughts
📝 Summary:
Large reasoning models' inference latency can be reduced by routing reasoning steps to larger models based on the entropy of their first token, enabling efficient collaborative inference without addit...
🔹 Publication Date: Published on Jan 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05110
• PDF: https://arxiv.org/pdf/2601.05110
• Github: https://github.com/Zengwh02/GlimpRouter
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📝 Summary:
Large reasoning models' inference latency can be reduced by routing reasoning steps to larger models based on the entropy of their first token, enabling efficient collaborative inference without addit...
🔹 Publication Date: Published on Jan 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05110
• PDF: https://arxiv.org/pdf/2601.05110
• Github: https://github.com/Zengwh02/GlimpRouter
==================================
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✨OpenTinker: Separating Concerns in Agentic Reinforcement Learning
📝 Summary:
OpenTinker provides a modular infrastructure for reinforcement learning of large language model agents with separated components and managed execution runtime. AI-generated summary We introduce OpenTi...
🔹 Publication Date: Published on Jan 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2601.07376
• PDF: https://arxiv.org/pdf/2601.07376
• Project Page: https://open-tinker.github.io/opentinker-page/
• Github: https://github.com/open-tinker/OpenTinker
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📝 Summary:
OpenTinker provides a modular infrastructure for reinforcement learning of large language model agents with separated components and managed execution runtime. AI-generated summary We introduce OpenTi...
🔹 Publication Date: Published on Jan 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2601.07376
• PDF: https://arxiv.org/pdf/2601.07376
• Project Page: https://open-tinker.github.io/opentinker-page/
• Github: https://github.com/open-tinker/OpenTinker
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✨On the Fallacy of Global Token Perplexity in Spoken Language Model Evaluation
📝 Summary:
Speech models trained on raw audio can generate appropriate content while maintaining speaker and emotion attributes, but traditional text-based evaluation methods underestimate speech characteristics...
🔹 Publication Date: Published on Jan 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.06329
• PDF: https://arxiv.org/pdf/2601.06329
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📝 Summary:
Speech models trained on raw audio can generate appropriate content while maintaining speaker and emotion attributes, but traditional text-based evaluation methods underestimate speech characteristics...
🔹 Publication Date: Published on Jan 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.06329
• PDF: https://arxiv.org/pdf/2601.06329
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✨Are LLM Decisions Faithful to Verbal Confidence?
📝 Summary:
Large language models exhibit a disconnect between their expressed uncertainty and strategic decision-making under varying penalty conditions, failing to adjust abstention policies even when optimal. ...
🔹 Publication Date: Published on Jan 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07767
• PDF: https://arxiv.org/pdf/2601.07767
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📝 Summary:
Large language models exhibit a disconnect between their expressed uncertainty and strategic decision-making under varying penalty conditions, failing to adjust abstention policies even when optimal. ...
🔹 Publication Date: Published on Jan 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07767
• PDF: https://arxiv.org/pdf/2601.07767
==================================
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✨Codified Foreshadowing-Payoff Text Generation
📝 Summary:
Large language models struggle with maintaining long-range narrative dependencies, but a new framework called CFPG addresses this by structuring narrative continuity through executable causal predicat...
🔹 Publication Date: Published on Jan 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07033
• PDF: https://arxiv.org/pdf/2601.07033
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📝 Summary:
Large language models struggle with maintaining long-range narrative dependencies, but a new framework called CFPG addresses this by structuring narrative continuity through executable causal predicat...
🔹 Publication Date: Published on Jan 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07033
• PDF: https://arxiv.org/pdf/2601.07033
==================================
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