✨Benchmarking Diversity in Image Generation via Attribute-Conditional Human Evaluation
📝 Summary:
This paper introduces a framework to robustly evaluate diversity in text-to-image models. It uses a novel human evaluation template, curated prompts with variation factors, and systematic analysis of image embeddings to rank models and identify diversity weaknesses.
🔹 Publication Date: Published on Nov 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10547
• PDF: https://arxiv.org/pdf/2511.10547
==================================
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#ImageGeneration #TextToImage #AIDiversity #Benchmarking #HumanEvaluation
📝 Summary:
This paper introduces a framework to robustly evaluate diversity in text-to-image models. It uses a novel human evaluation template, curated prompts with variation factors, and systematic analysis of image embeddings to rank models and identify diversity weaknesses.
🔹 Publication Date: Published on Nov 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10547
• PDF: https://arxiv.org/pdf/2511.10547
==================================
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#ImageGeneration #TextToImage #AIDiversity #Benchmarking #HumanEvaluation
✨Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following
📝 Summary:
AdvancedIF benchmark and RIFL pipeline improve instruction-following capabilities in large language models by using expert-curated rubrics and reinforcement learning techniques. AI-generated summary R...
🔹 Publication Date: Published on Nov 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10507
• PDF: https://arxiv.org/pdf/2511.10507
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
AdvancedIF benchmark and RIFL pipeline improve instruction-following capabilities in large language models by using expert-curated rubrics and reinforcement learning techniques. AI-generated summary R...
🔹 Publication Date: Published on Nov 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10507
• PDF: https://arxiv.org/pdf/2511.10507
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
✨AffordBot: 3D Fine-grained Embodied Reasoning via Multimodal Large Language Models
📝 Summary:
AffordBot uses MLLMs and chain-of-thought reasoning for fine-grained 3D embodied reasoning. It predicts affordance elements' location, motion type, and axis in 3D scenes per instructions. It achieves state-of-the-art by projecting 3D elements for 2D MLLMs.
🔹 Publication Date: Published on Nov 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10017
• PDF: https://arxiv.org/pdf/2511.10017
==================================
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#AffordBot #MLLM #EmbodiedAI #3DReasoning #Robotics
📝 Summary:
AffordBot uses MLLMs and chain-of-thought reasoning for fine-grained 3D embodied reasoning. It predicts affordance elements' location, motion type, and axis in 3D scenes per instructions. It achieves state-of-the-art by projecting 3D elements for 2D MLLMs.
🔹 Publication Date: Published on Nov 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10017
• PDF: https://arxiv.org/pdf/2511.10017
==================================
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#AffordBot #MLLM #EmbodiedAI #3DReasoning #Robotics
✨SliderEdit: Continuous Image Editing with Fine-Grained Instruction Control
📝 Summary:
SliderEdit enables continuous, fine-grained control over image editing instructions by using low-rank adaptation matrices, improving edit controllability, visual consistency, and user steerability. AI...
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09715
• PDF: https://arxiv.org/pdf/2511.09715
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
SliderEdit enables continuous, fine-grained control over image editing instructions by using low-rank adaptation matrices, improving edit controllability, visual consistency, and user steerability. AI...
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09715
• PDF: https://arxiv.org/pdf/2511.09715
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
✨ResearchRubrics: A Benchmark of Prompts and Rubrics For Evaluating Deep Research Agents
📝 Summary:
ResearchRubrics is a benchmark for evaluating deep research agents, using expert rubrics to assess their factual grounding, reasoning, and clarity across diverse, complex tasks. AI-generated summary D...
🔹 Publication Date: Published on Nov 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07685
• PDF: https://arxiv.org/pdf/2511.07685
✨ Datasets citing this paper:
• https://huggingface.co/datasets/ScaleAI/researchrubrics
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
ResearchRubrics is a benchmark for evaluating deep research agents, using expert rubrics to assess their factual grounding, reasoning, and clarity across diverse, complex tasks. AI-generated summary D...
🔹 Publication Date: Published on Nov 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07685
• PDF: https://arxiv.org/pdf/2511.07685
✨ Datasets citing this paper:
• https://huggingface.co/datasets/ScaleAI/researchrubrics
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
✨PAN: A World Model for General, Interactable, and Long-Horizon World Simulation
📝 Summary:
PAN is a general interactable world model that predicts future states through high-quality action-conditioned video simulation. It uses a GLP architecture combining LLM-based latent dynamics with a video diffusion decoder for detailed long-term coherent results enabling reasoning and acting.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09057
• PDF: https://arxiv.org/pdf/2511.09057
==================================
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#WorldModels #AI #Simulation #GenerativeAI #Robotics
📝 Summary:
PAN is a general interactable world model that predicts future states through high-quality action-conditioned video simulation. It uses a GLP architecture combining LLM-based latent dynamics with a video diffusion decoder for detailed long-term coherent results enabling reasoning and acting.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09057
• PDF: https://arxiv.org/pdf/2511.09057
==================================
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#WorldModels #AI #Simulation #GenerativeAI #Robotics
❤1
✨Hail to the Thief: Exploring Attacks and Defenses in Decentralised GRPO
📝 Summary:
This study identifies and demonstrates adversarial attacks in decentralized GRPO for LLMs, achieving 100% success rates by injecting malicious tokens. It also proposes effective defense mechanisms that can stop these attacks completely.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09780
• PDF: https://arxiv.org/pdf/2511.09780
==================================
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#LLMs #AdversarialAttacks #AISecurity #DecentralizedAI #GRPO
📝 Summary:
This study identifies and demonstrates adversarial attacks in decentralized GRPO for LLMs, achieving 100% success rates by injecting malicious tokens. It also proposes effective defense mechanisms that can stop these attacks completely.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09780
• PDF: https://arxiv.org/pdf/2511.09780
==================================
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✓ https://news.1rj.ru/str/DataScienceT
#LLMs #AdversarialAttacks #AISecurity #DecentralizedAI #GRPO
❤1
✨Solving a Million-Step LLM Task with Zero Errors
📝 Summary:
MAKER solves million-step LLM tasks with zero errors. It uses extreme task decomposition for microagents and applies error correction at each step with multi-agent voting. This offers a new scalable approach for complex LLM processes.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09030
• PDF: https://arxiv.org/pdf/2511.09030
==================================
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✓ https://news.1rj.ru/str/DataScienceT
#LLM #AI #ErrorCorrection #MultiAgent #TaskDecomposition
📝 Summary:
MAKER solves million-step LLM tasks with zero errors. It uses extreme task decomposition for microagents and applies error correction at each step with multi-agent voting. This offers a new scalable approach for complex LLM processes.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09030
• PDF: https://arxiv.org/pdf/2511.09030
==================================
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#LLM #AI #ErrorCorrection #MultiAgent #TaskDecomposition
✨CC30k: A Citation Contexts Dataset for Reproducibility-Oriented Sentiment Analysis
📝 Summary:
CC30k is a new dataset of 30,000 machine learning paper citation contexts, labeled with reproducibility-oriented sentiments. It enables large language models to better predict paper reproducibility, filling a crucial gap in computational reproducibility studies.
🔹 Publication Date: Published on Nov 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07790
• PDF: https://arxiv.org/pdf/2511.07790
✨ Datasets citing this paper:
• https://huggingface.co/datasets/rochanaro/CC30k
==================================
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#MachineLearning #Reproducibility #LLM #SentimentAnalysis #DataScience
📝 Summary:
CC30k is a new dataset of 30,000 machine learning paper citation contexts, labeled with reproducibility-oriented sentiments. It enables large language models to better predict paper reproducibility, filling a crucial gap in computational reproducibility studies.
🔹 Publication Date: Published on Nov 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07790
• PDF: https://arxiv.org/pdf/2511.07790
✨ Datasets citing this paper:
• https://huggingface.co/datasets/rochanaro/CC30k
==================================
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#MachineLearning #Reproducibility #LLM #SentimentAnalysis #DataScience
❤1
✨MM-CRITIC: A Holistic Evaluation of Large Multimodal Models as Multimodal Critique
📝 Summary:
MM-CRITIC is a new benchmark evaluating Large Multimodal Models critique abilities across various dimensions and tasks. It uses expert-informed ground answers and GPT-4o for reliable scoring. This benchmark provides a comprehensive assessment of leading LMMs' critique capabilities.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09067
• PDF: https://arxiv.org/pdf/2511.09067
==================================
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#LMMs #MultimodalAI #AIEvaluation #Benchmarking #AIResearch
📝 Summary:
MM-CRITIC is a new benchmark evaluating Large Multimodal Models critique abilities across various dimensions and tasks. It uses expert-informed ground answers and GPT-4o for reliable scoring. This benchmark provides a comprehensive assessment of leading LMMs' critique capabilities.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09067
• PDF: https://arxiv.org/pdf/2511.09067
==================================
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#LMMs #MultimodalAI #AIEvaluation #Benchmarking #AIResearch
✨Beyond Outlining: Heterogeneous Recursive Planning for Adaptive Long-form Writing with Language Models
📝 Summary:
This paper proposes an AI agent framework for adaptive long-form writing. It uses recursive task decomposition and dynamically integrates retrieval, reasoning, and composition, overcoming rigid outline-based methods. The framework consistently outperforms state-of-the-art approaches.
🔹 Publication Date: Published on Mar 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2503.08275
• PDF: https://arxiv.org/pdf/2503.08275
• Github: https://github.com/principia-ai/WriteHERE
==================================
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#AI #LanguageModels #LongformWriting #NLP #GenerativeAI
📝 Summary:
This paper proposes an AI agent framework for adaptive long-form writing. It uses recursive task decomposition and dynamically integrates retrieval, reasoning, and composition, overcoming rigid outline-based methods. The framework consistently outperforms state-of-the-art approaches.
🔹 Publication Date: Published on Mar 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2503.08275
• PDF: https://arxiv.org/pdf/2503.08275
• Github: https://github.com/principia-ai/WriteHERE
==================================
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#AI #LanguageModels #LongformWriting #NLP #GenerativeAI
❤1
🤖🧠 Steel Browser: The Open-Source Browser API Powering AI Agents and Automation
🗓️ 16 Nov 2025
📚 AI News & Trends
The evolution of artificial intelligence has ushered in a new era of automation where AI agents can perform complex digital tasks with minimal human intervention. However, one of the biggest challenges for developers building these systems is browser automation managing sessions, proxies, cookies and debugging environments. This is where Steel Browser comes into play. Steel ...
#SteelBrowser #OpenSource #BrowserAutomation #AIAgents #WebScraping #DigitalAutomation
🗓️ 16 Nov 2025
📚 AI News & Trends
The evolution of artificial intelligence has ushered in a new era of automation where AI agents can perform complex digital tasks with minimal human intervention. However, one of the biggest challenges for developers building these systems is browser automation managing sessions, proxies, cookies and debugging environments. This is where Steel Browser comes into play. Steel ...
#SteelBrowser #OpenSource #BrowserAutomation #AIAgents #WebScraping #DigitalAutomation
👍1🔥1
✨Transformer Explainer: Interactive Learning of Text-Generative Models
📝 Summary:
Transformer Explainer is an interactive web tool for non-experts to understand the GPT-2 model. It allows real-time experimentation with user input, visualizing how internal components predict text. This broadens access to education about modern generative AI.
🔹 Publication Date: Published on Aug 8, 2024
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2408.04619
• PDF: https://arxiv.org/pdf/2408.04619
• Project Page: https://poloclub.github.io/transformer-explainer/
• Github: https://github.com/helblazer811/ManimML
==================================
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#AI #GenerativeAI #Transformers #AIeducation #ExplainableAI
📝 Summary:
Transformer Explainer is an interactive web tool for non-experts to understand the GPT-2 model. It allows real-time experimentation with user input, visualizing how internal components predict text. This broadens access to education about modern generative AI.
🔹 Publication Date: Published on Aug 8, 2024
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2408.04619
• PDF: https://arxiv.org/pdf/2408.04619
• Project Page: https://poloclub.github.io/transformer-explainer/
• Github: https://github.com/helblazer811/ManimML
==================================
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#AI #GenerativeAI #Transformers #AIeducation #ExplainableAI
❤🔥1👍1
🤖🧠 Skyvern: The Future of Browser Automation Powered by AI and Computer Vision
🗓️ 16 Nov 2025
📚 AI News & Trends
In today’s fast-evolving digital landscape, automation plays a crucial role in enhancing productivity, efficiency and innovation. Yet, traditional browser automation tools often struggle with complexity, maintenance and reliability. They rely heavily on DOM parsing, XPaths and rigid noscripts that easily break when websites change their layout. Enter Skyvern, an open-source, AI-driven browser automation platform developed ...
#Skyvern #BrowserAutomation #AIDriven #ComputerVision #OpenSource #WebAutomation
🗓️ 16 Nov 2025
📚 AI News & Trends
In today’s fast-evolving digital landscape, automation plays a crucial role in enhancing productivity, efficiency and innovation. Yet, traditional browser automation tools often struggle with complexity, maintenance and reliability. They rely heavily on DOM parsing, XPaths and rigid noscripts that easily break when websites change their layout. Enter Skyvern, an open-source, AI-driven browser automation platform developed ...
#Skyvern #BrowserAutomation #AIDriven #ComputerVision #OpenSource #WebAutomation
❤🔥1❤1👍1
🤖🧠 OpenAI Evals: The Framework Transforming LLM Evaluation and Benchmarking
🗓️ 16 Nov 2025
📚 AI News & Trends
As large language models (LLMs) continue to reshape industries from education and healthcare to marketing and software development – the need for reliable evaluation methods has never been greater. With new models constantly emerging, developers and researchers require a standardized system to test, compare and understand model performance across real-world scenarios. This is where OpenAI ...
#OpenAIEvals #LLMEvaluation #Benchmarking #LargeLanguageModels #AIResearch #ModelEvaluation
🗓️ 16 Nov 2025
📚 AI News & Trends
As large language models (LLMs) continue to reshape industries from education and healthcare to marketing and software development – the need for reliable evaluation methods has never been greater. With new models constantly emerging, developers and researchers require a standardized system to test, compare and understand model performance across real-world scenarios. This is where OpenAI ...
#OpenAIEvals #LLMEvaluation #Benchmarking #LargeLanguageModels #AIResearch #ModelEvaluation
❤1
🤖🧠 Context Engineering 2.0: Redefining Human–Machine Understanding
🗓️ 16 Nov 2025
📚 AI News & Trends
As artificial intelligence advances, machines are becoming increasingly capable of understanding and responding to human language. Yet, one crucial challenge remains how can machines truly understand the context behind human intentions? This question forms the foundation of context engineering, a discipline that focuses on designing, organizing and managing contextual information so that AI systems can ...
#ContextEngineering #AIEducation #HumanMachineUnderstanding #AIContext #NaturalLanguageProcessing #AIModels
🗓️ 16 Nov 2025
📚 AI News & Trends
As artificial intelligence advances, machines are becoming increasingly capable of understanding and responding to human language. Yet, one crucial challenge remains how can machines truly understand the context behind human intentions? This question forms the foundation of context engineering, a discipline that focuses on designing, organizing and managing contextual information so that AI systems can ...
#ContextEngineering #AIEducation #HumanMachineUnderstanding #AIContext #NaturalLanguageProcessing #AIModels
✨EmoVid: A Multimodal Emotion Video Dataset for Emotion-Centric Video Understanding and Generation
📝 Summary:
EmoVid is a new multimodal, emotion-annotated video dataset designed for creative media like cartoons and movies. It bridges emotion understanding with video generation, significantly improving emotional expression and quality in generated videos. EmoVid establishes a new benchmark for affective ...
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.11002
• PDF: https://arxiv.org/pdf/2511.11002
==================================
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#EmoVid #MultimodalAI #EmotionAI #VideoGeneration #VideoUnderstanding
📝 Summary:
EmoVid is a new multimodal, emotion-annotated video dataset designed for creative media like cartoons and movies. It bridges emotion understanding with video generation, significantly improving emotional expression and quality in generated videos. EmoVid establishes a new benchmark for affective ...
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.11002
• PDF: https://arxiv.org/pdf/2511.11002
==================================
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#EmoVid #MultimodalAI #EmotionAI #VideoGeneration #VideoUnderstanding
✨Virtual Width Networks
📝 Summary:
Virtual Width Networks VWN enhance model efficiency by expanding representational width without increasing computational cost. VWN accelerates optimization and improves loss reduction, showing a log-linear scaling relation between virtual width and loss.
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.11238
• PDF: https://arxiv.org/pdf/2511.11238
==================================
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#NeuralNetworks #DeepLearning #ModelEfficiency #MachineLearning #AI
📝 Summary:
Virtual Width Networks VWN enhance model efficiency by expanding representational width without increasing computational cost. VWN accelerates optimization and improves loss reduction, showing a log-linear scaling relation between virtual width and loss.
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.11238
• PDF: https://arxiv.org/pdf/2511.11238
==================================
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#NeuralNetworks #DeepLearning #ModelEfficiency #MachineLearning #AI
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✨GGBench: A Geometric Generative Reasoning Benchmark for Unified Multimodal Models
📝 Summary:
GGBench is a new benchmark for evaluating geometric generative reasoning in unified multimodal models. It addresses a critical gap by assessing integrated cognitive processes, requiring language comprehension and precise visual generation to actively construct solutions. This sets a rigorous stan...
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.11134
• PDF: https://arxiv.org/pdf/2511.11134
==================================
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#GGBench #MultimodalAI #GeometricReasoning #GenerativeAI #AIResearch
📝 Summary:
GGBench is a new benchmark for evaluating geometric generative reasoning in unified multimodal models. It addresses a critical gap by assessing integrated cognitive processes, requiring language comprehension and precise visual generation to actively construct solutions. This sets a rigorous stan...
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.11134
• PDF: https://arxiv.org/pdf/2511.11134
==================================
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#GGBench #MultimodalAI #GeometricReasoning #GenerativeAI #AIResearch
✨DiscoX: Benchmarking Discourse-Level Translation task in Expert Domains
📝 Summary:
A new benchmark, DiscoX, and evaluation system, Metric-S, are introduced for discourse-level, expert Chinese-English translation. Findings show advanced LLMs still fall short of human performance, underscoring challenges in professional machine translation.
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10984
• PDF: https://arxiv.org/pdf/2511.10984
==================================
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#MachineTranslation #NLP #LLM #Benchmarking #AI
📝 Summary:
A new benchmark, DiscoX, and evaluation system, Metric-S, are introduced for discourse-level, expert Chinese-English translation. Findings show advanced LLMs still fall short of human performance, underscoring challenges in professional machine translation.
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.10984
• PDF: https://arxiv.org/pdf/2511.10984
==================================
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#MachineTranslation #NLP #LLM #Benchmarking #AI
✨CATS-V2V: A Real-World Vehicle-to-Vehicle Cooperative Perception Dataset with Complex Adverse Traffic Scenarios
📝 Summary:
CATS-V2V is a new real-world dataset for V2V cooperative perception, focusing on complex adverse traffic scenarios. It provides extensive synchronized sensor data, including LiDAR and cameras, from two vehicles across diverse conditions. This dataset supports autonomous driving research.
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.11168
• PDF: https://arxiv.org/pdf/2511.11168
==================================
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#V2V #AutonomousDriving #CooperativePerception #Dataset #ADAS
📝 Summary:
CATS-V2V is a new real-world dataset for V2V cooperative perception, focusing on complex adverse traffic scenarios. It provides extensive synchronized sensor data, including LiDAR and cameras, from two vehicles across diverse conditions. This dataset supports autonomous driving research.
🔹 Publication Date: Published on Nov 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.11168
• PDF: https://arxiv.org/pdf/2511.11168
==================================
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#V2V #AutonomousDriving #CooperativePerception #Dataset #ADAS