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πŸ”Ή Title: MMTok: Multimodal Coverage Maximization for Efficient Inference of VLMs

πŸ”Ή Publication Date: Published on Aug 25

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.18264
β€’ PDF: https://arxiv.org/pdf/2508.18264
β€’ Project Page: https://project.ironieser.cc/mmtok

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πŸ”Ή Title: Hermes 4 Technical Report

πŸ”Ή Publication Date: Published on Aug 25

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.18255
β€’ PDF: https://arxiv.org/pdf/2508.18255
β€’ Project Page: https://hermes4.nousresearch.com/

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πŸ”Ή Title: Semantic Diffusion Posterior Sampling for Cardiac Ultrasound Dehazing

πŸ”Ή Publication Date: Published on Aug 24

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.17326
β€’ PDF: https://arxiv.org/pdf/2508.17326
β€’ Github: https://github.com/tristan-deep/semantic-diffusion-echo-dehazing

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πŸ”Ή Title: Understanding Tool-Integrated Reasoning

πŸ”Ή Publication Date: Published on Aug 26

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.19201
β€’ PDF: https://arxiv.org/pdf/2508.19201
β€’ Project Page: https://zhongwenxu.notion.site/Understanding-Tool-Integrated-Reasoning-2551c4e140e3805489fadcc802a1ea83

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πŸ”Ή Title: Spacer: Towards Engineered Scientific Inspiration

πŸ”Ή Publication Date: Published on Aug 25

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.17661
β€’ PDF: https://arxiv.org/pdf/2508.17661
β€’ Github: https://github.com/asteromorph-corp/spacer

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πŸ”Ή Title: VoxHammer: Training-Free Precise and Coherent 3D Editing in Native 3D Space

πŸ”Ή Publication Date: Published on Aug 26

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.19247
β€’ PDF: https://arxiv.org/pdf/2508.19247
β€’ Project Page: https://huanngzh.github.io/VoxHammer-Page/
β€’ Github: https://github.com/Nelipot-Lee/VoxHammer/Edit3D-Bench

πŸ”Ή Datasets citing this paper:
β€’ https://huggingface.co/datasets/huanngzh/Edit3D-Bench

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πŸ”Ή Title: Unraveling the cognitive patterns of Large Language Models through module communities

πŸ”Ή Publication Date: Published on Aug 25

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.18192
β€’ PDF: https://arxiv.org/pdf/2508.18192

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πŸ”Ή Title: OmniHuman-1.5: Instilling an Active Mind in Avatars via Cognitive Simulation

πŸ”Ή Publication Date: Published on Aug 26

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.19209
β€’ PDF: https://arxiv.org/pdf/2508.19209
β€’ Project Page: https://omnihuman-lab.github.io/v1_5/

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πŸ”Ή Title: UltraMemV2: Memory Networks Scaling to 120B Parameters with Superior Long-Context Learning

πŸ”Ή Publication Date: Published on Aug 26

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.18756
β€’ PDF: https://arxiv.org/pdf/2508.18756
β€’ Github: https://github.com/ZihaoHuang-notabot/Ultra-Sparse-Memory-Network

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πŸ”Ή Title: CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics

πŸ”Ή Publication Date: Published on Aug 25

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.18124
β€’ PDF: https://arxiv.org/pdf/2508.18124
β€’ Github: https://github.com/CMPhysBench/CMPhysBench%5D

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πŸ”Ή Title: TreePO: Bridging the Gap of Policy Optimization and Efficacy and Inference Efficiency with Heuristic Tree-based Modeling

πŸ”Ή Publication Date: Published on Aug 24

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.17445
β€’ PDF: https://arxiv.org/pdf/2508.17445

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πŸ”Ή Title: Wan-S2V: Audio-Driven Cinematic Video Generation

πŸ”Ή Publication Date: Published on Aug 26

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.18621
β€’ PDF: https://arxiv.org/pdf/2508.18621

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πŸ”Ή Title: QueryBandits for Hallucination Mitigation: Exploiting Semantic Features for No-Regret Rewriting

πŸ”Ή Publication Date: Published on Aug 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.16697
β€’ PDF: https://arxiv.org/pdf/2508.16697

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πŸ”Ή Title: ThinkDial: An Open Recipe for Controlling Reasoning Effort in Large Language Models

πŸ”Ή Publication Date: Published on Aug 26

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2502.18080
β€’ PDF: https://arxiv.org/pdf/2508.18773

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πŸ”Ή Title: Training Language Model Agents to Find Vulnerabilities with CTF-Dojo

πŸ”Ή Publication Date: Published on Aug 25

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.00910
β€’ PDF: https://arxiv.org/pdf/2508.18370

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πŸ”Ή Title: FastMesh:Efficient Artistic Mesh Generation via Component Decoupling

πŸ”Ή Publication Date: Published on Aug 26

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.19188
β€’ PDF: https://arxiv.org/pdf/2508.19188
β€’ Project Page: https://jhkim0759.github.io/projects/FastMesh/

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πŸ”Ή Title: Evaluating, Synthesizing, and Enhancing for Customer Support Conversation

πŸ”Ή Publication Date: Published on Aug 6

πŸ”Ή Abstract: A structured framework and datasets for training customer service agents using well-defined support strategies improve the quality of customer support interactions and problem resolution. AI-generated summary Effective customer support requires not only accurate problem solving but also structured and empathetic communication aligned with professional standards. However, existing dialogue datasets often lack strategic guidance, and real-world service data is difficult to access and annotate. To address this, we introduce the task of Customer Support Conversation (CSC), aimed at training customer service agents to respond using well-defined support strategies. We propose a structured CSC framework grounded in COPC guidelines , defining five conversational stages and twelve strategies to guide high-quality interactions. Based on this, we construct CSConv , an evaluation dataset of 1,855 real-world customer-agent conversations rewritten using LLMs to reflect deliberate strategy use, and annotated accordingly. Additionally, we develop a role-playing approach that simulates strategy-rich conversations using LLM-powered roles aligned with the CSC framework, resulting in the training dataset RoleCS . Experiments show that fine-tuning strong LLMs on RoleCS significantly improves their ability to generate high-quality, strategy-aligned responses on CSConv . Human evaluations further confirm gains in problem resolution. All code and data will be made publicly available at https://github.com/aliyun/qwen-dianjin.

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.04423

β€’ PDF: https://arxiv.org/pdf/2508.04423

β€’ Github: https://github.com/aliyun/qwen-dianjin

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πŸ”Ή Title: Autoregressive Universal Video Segmentation Model

πŸ”Ή Publication Date: Published on Aug 26

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.19242
β€’ PDF: https://arxiv.org/pdf/2508.19242

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πŸ”Ή Title: MovieCORE: COgnitive REasoning in Movies

πŸ”Ή Publication Date: Published on Aug 26

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.19026
β€’ PDF: https://arxiv.org/pdf/2508.19026
β€’ Github: https://joslefaure.github.io/assets/html/moviecore.html

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πŸ”Ή Title: ObjFiller-3D: Consistent Multi-view 3D Inpainting via Video Diffusion Models

πŸ”Ή Publication Date: Published on Aug 25

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2508.18271
β€’ PDF: https://arxiv.org/pdf/2508.18271
β€’ Project Page: https://objfiller3d.github.io/
β€’ Github: https://github.com/objfiller3d/ObjFiller-3D

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