ML Research Hub – Telegram
ML Research Hub
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

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Error-Free Linear Attention is a Free Lunch: Exact Solution from Continuous-Time Dynamics

📝 Summary:
Error-Free Linear Attention (EFLA) is a stable, parallelizable, and theoretically sound linear-time attention mechanism that outperforms DeltaNet in language modeling and downstream tasks. AI-generate...

🔹 Publication Date: Published on Dec 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12602
• PDF: https://arxiv.org/pdf/2512.12602
• Github: https://github.com/declare-lab/EFLA

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NL2Repo-Bench: Towards Long-Horizon Repository Generation Evaluation of Coding Agents

📝 Summary:
NL2Repo Bench evaluates long-horizon software development capabilities of coding agents by assessing their ability to generate complete Python libraries from natural-language requirements. AI-generate...

🔹 Publication Date: Published on Dec 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12730
• PDF: https://arxiv.org/pdf/2512.12730
• Project Page: https://github.com/multimodal-art-projection/NL2RepoBench
• Github: https://github.com/multimodal-art-projection/NL2RepoBench

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LongVie 2: Multimodal Controllable Ultra-Long Video World Model

📝 Summary:
LongVie 2, an end-to-end autoregressive framework, enhances controllability, visual quality, and temporal consistency in video world models through three progressive training stages. AI-generated summ...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13604
• PDF: https://arxiv.org/pdf/2512.13604
• Project Page: https://vchitect.github.io/LongVie2-project/
• Github: https://github.com/Vchitect/LongVie

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V-REX: Benchmarking Exploratory Visual Reasoning via Chain-of-Questions

📝 Summary:
The V-REX evaluation suite assesses vision-language models' multi-step reasoning and exploration capabilities through a Chain-of-Questions framework, revealing their strengths and weaknesses in planni...

🔹 Publication Date: Published on Dec 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11995
• PDF: https://arxiv.org/pdf/2512.11995
• Github: https://github.com/tianyi-lab/VREX

Datasets citing this paper:
https://huggingface.co/datasets/umd-zhou-lab/V-REX

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Image Diffusion Preview with Consistency Solver

📝 Summary:
Diffusion Preview uses ConsistencySolver, a high-order trainable solver, to improve quality and consistency in low-step image generation, enhancing interactive user experiences. AI-generated summary T...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13592
• PDF: https://arxiv.org/pdf/2512.13592
• Github: https://github.com/G-U-N/consolver

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Video Reality Test: Can AI-Generated ASMR Videos fool VLMs and Humans?

📝 Summary:
The Video Reality Test benchmark evaluates the realism and detection of AI-generated ASMR videos with audio, revealing that even the best models can deceive VLMs and humans, highlighting limitations i...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13281
• PDF: https://arxiv.org/pdf/2512.13281
• Project Page: https://video-reality-test.github.io/
• Github: https://github.com/video-reality-test/video-reality-test

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Aesthetic Alignment Risks Assimilation: How Image Generation and Reward Models Reinforce Beauty Bias and Ideological "Censorship"

📝 Summary:
State-of-the-art image generation and reward models exhibit bias towards conventional aesthetics, often failing to produce anti-aesthetic images as requested, thus compromising user autonomy and aesth...

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11883
• PDF: https://arxiv.org/pdf/2512.11883

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KlingAvatar 2.0 Technical Report

📝 Summary:
KlingAvatar 2.0 addresses inefficiencies in generating long-duration, high-resolution videos by using a spatio-temporal cascade framework with a Co-Reasoning Director and Negative Director for improve...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13313
• PDF: https://arxiv.org/pdf/2512.13313
• Project Page: https://app.klingai.com/global/ai-human/image/new/

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QwenLong-L1.5: Post-Training Recipe for Long-Context Reasoning and Memory Management

📝 Summary:
QwenLong-L1.5 enhances long-context reasoning through data synthesis, stabilized reinforcement learning, and memory-augmented architecture, achieving superior performance on benchmarks and general dom...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12967
• PDF: https://arxiv.org/pdf/2512.12967

🔹 Models citing this paper:
https://huggingface.co/Tongyi-Zhiwen/QwenLong-L1.5-30B-A3B

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START: Spatial and Textual Learning for Chart Understanding

📝 Summary:
START enhances multimodal large language models by integrating spatial and textual learning through chart-element grounding and chart-to-code generation, improving chart understanding and performance ...

🔹 Publication Date: Published on Dec 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.07186
• PDF: https://arxiv.org/pdf/2512.07186
• Github: https://github.com/dragonlzm/START

🔹 Models citing this paper:
https://huggingface.co/zhuomingliu/START

Datasets citing this paper:
https://huggingface.co/datasets/zhuomingliu/CS-Bench
https://huggingface.co/datasets/zhuomingliu/START-Dataset
https://huggingface.co/datasets/zhuomingliu/START_eval

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Memory in the Age of AI Agents

📝 Summary:
This survey provides an updated overview of agent memory research, distinguishing its forms, functions, and dynamics, and highlights emerging research directions. AI-generated summary Memory has emerg...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13564
• PDF: https://arxiv.org/pdf/2512.13564

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ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding

📝 Summary:
ReFusion, a novel masked diffusion model, improves performance and efficiency by using slot-based parallel decoding, achieving superior results compared to autoregressive models and traditional masked...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13586
• PDF: https://arxiv.org/pdf/2512.13586
• Github: https://github.com/ML-GSAI/ReFusion

🔹 Models citing this paper:
https://huggingface.co/GSAI-ML/ReFusion

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Spatial-Aware VLA Pretraining through Visual-Physical Alignment from Human Videos

📝 Summary:
A Spatial-Aware VLA Pretraining paradigm improves 3D spatial understanding in robots by aligning 2D visual inputs with 3D actions using dual-encoder architecture with a 3D visual encoder. AI-generated...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13080
• PDF: https://arxiv.org/pdf/2512.13080
• Project Page: https://beingbeyond.github.io/VIPA-VLA/
• Github: https://beingbeyond.github.io/VIPA-VLA

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Toward Ambulatory Vision: Learning Visually-Grounded Active View Selection

📝 Summary:
VG-AVS, a task and framework fine-tunes VLMs to select the most informative next viewpoint for visual question answering, enhancing performance and generalization. AI-generated summary Vision Language...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13250
• PDF: https://arxiv.org/pdf/2512.13250
• Project Page: https://active-view-selection.github.io
• Github: https://github.com/KAIST-Visual-AI-Group/VG-AVS

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LitePT: Lighter Yet Stronger Point Transformer

📝 Summary:
LitePT combines early convolutions and deep attention for 3D point clouds, using PointROPE positional encoding. This new model is highly efficient, outperforming state-of-the-art while using fewer resources.

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13689
• PDF: https://arxiv.org/pdf/2512.13689
• Project Page: https://litept.github.io/
• Github: https://github.com/prs-eth/LitePT

🔹 Models citing this paper:
https://huggingface.co/yuanwenyue/LitePT

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VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer

📝 Summary:
AEGIS, a Vision-Language-Safe Action architecture with a plug-and-play safety constraint layer using control barrier functions, enhances safety and performance in robotic manipulation tasks. AI-genera...

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11891
• PDF: https://arxiv.org/pdf/2512.11891
• Github: https://vlsa-aegis.github.io

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Towards Interactive Intelligence for Digital Humans

📝 Summary:
Interactive Intelligence, realized through Mio framework, enables advanced digital humans with personality, adaptive interactions, and self-evolution, surpassing current benchmarks. AI-generated summa...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13674
• PDF: https://arxiv.org/pdf/2512.13674
• Project Page: https://shandaai.github.io/project_mio_page/

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DiffusionBrowser: Interactive Diffusion Previews via Multi-Branch Decoders

📝 Summary:
DiffusionBrowser is a lightweight decoder for interactive video previews during diffusion model denoising. It enables fast multi-modal previews, enhancing user control and revealing how video details are composed internally.

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13690
• PDF: https://arxiv.org/pdf/2512.13690
• Github: https://susunghong.github.io/DiffusionBrowser

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

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RecTok: Reconstruction Distillation along Rectified Flow

📝 Summary:
RecTok improves diffusion models by enriching forward flow semantics and enhancing reconstruction, achieving state-of-the-art results with high-dimensional visual tokenizers. AI-generated summary Visu...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13421
• PDF: https://arxiv.org/pdf/2512.13421
• Project Page: https://shi-qingyu.github.io/rectok.github.io/
• Github: https://github.com/Shi-qingyu/RecTok

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Self-Supervised Prompt Optimization

📝 Summary:
A self-supervised framework optimizes prompts for both closed and open-ended tasks by evaluating LLM outputs without external references, reducing costs and required data. AI-generated summary Well-de...

🔹 Publication Date: Published on Feb 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2502.06855
• PDF: https://arxiv.org/pdf/2502.06855
• Github: https://github.com/geekan/metagpt

Spaces citing this paper:
https://huggingface.co/spaces/XiangJinYu/SPO
https://huggingface.co/spaces/tang-x/SPO
https://huggingface.co/spaces/ositamiles/SPO

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

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