数据来源：HuggingFace Papers Latest Papers1. OmniDirector: General Multi-Shot Camera Cloning without Cross-Paired DataAbstract:Cloning camera motion from reference videos is an important task in video generation, as videos provide intuitive and precise control. Existing methods either directly use parametric representations that fail to handle multi-shot generation or synthesize cross-paired data, which suffer from data scarcity, resulting in poor performance in complicated camera motion cloning. T ...

数据来源：HuggingFace Papers Latest Papers1. LoopCoder-v2: Only Loop Once for Efficient Test-Time Computation ScalingAbstract:Looped Transformers scale latent computation by repeatedly applying shared blocks, but sequential looping increases latency and KV-cache memory with the loop count. Parallel loop Transformers (PLT) alleviate this cost through cross-loop position offsets (CLP) and shared-KV gated sliding-window attention, making loop count a practical design choice. We therefore study PLT loo ...

数据来源：HuggingFace Papers Latest Papers1. Moebius: 0.2B Lightweight Image Inpainting Framework with 10B-Level PerformanceAbstract:While 10B-level industrial foundation models have pushed the boundaries of image inpainting, their prohibitive computational costs severely hinder practical deployment. Constructing a highly optimized task-specific specialist offers a promising solution; however, extreme structural compression inevitably triggers a severe representation bottleneck. To conquer this, we ...

数据来源：HuggingFace Papers Latest Papers1. Moebius: 0.2B Lightweight Image Inpainting Framework with 10B-Level PerformanceAbstract:While 10B-level industrial foundation models have pushed the boundaries of image inpainting, their prohibitive computational costs severely hinder practical deployment. Constructing a highly optimized task-specific specialist offers a promising solution; however, extreme structural compression inevitably triggers a severe representation bottleneck. To conquer this, we ...

数据来源：HuggingFace Papers Latest Papers1. DanceOPD: On-Policy Generative Field DistillationAbstract:Modern image generation demands a single model that unifies diverse capabilities, including text-to-image (T2I), local editing, and global editing. However, these capabilities are rarely naturally aligned and often conflict. For instance, editing tends to degrade T2I performance, while global and local editing interfere with each other. Consequently, effectively composing these capabilities has be ...

数据来源：HuggingFace Papers Latest Papers1. AskChem: Claim-Centered Infrastructure for Chemistry Literature SynthesisAbstract:Chemistry literature synthesis often requires assembling specific findings scattered across many publications, yet existing literature-search systems primarily return ranked document lists. As a result, scientists and AI agents need to locate relevant information, verify their provenance, and assemble cross-paper answers manually. We present AskChem, a claim-centered infras ...

数据来源：HuggingFace Papers Latest Papers1. AskChem: Claim-Centered Infrastructure for Chemistry Literature SynthesisAbstract:Chemistry literature synthesis often requires assembling specific findings scattered across many publications, yet existing literature-search systems primarily return ranked document lists. As a result, scientists and AI agents need to locate relevant information, verify their provenance, and assemble cross-paper answers manually. We present AskChem, a claim-centered infras ...

数据来源：HuggingFace Papers Latest Papers1. MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce OperationsAbstract:Large language model agents are increasingly evaluated as autonomous tool users, yet most benchmarks focus on bounded tasks with immediate success criteria. Real-world deployments often require Long-Term Coherence, the capacity to preserve purposeful behavior across extended horizons while adapting decisions to accumulated evidence. Evaluating this capacity re ...

数据来源：ArXiv Domain LLM Domain Papers1. EDEN: A Large-Scale Corpus of Clinical Notes for ItalianAbstract:We present EDEN (Emergency Department Electronic Notes), a new and unique large-scale corpus of clinical notes produced in Emergency Departments of Italian hospitals. The corpus, in its current version, is composed of approximately 4 million clinical notes fully anonymized, covering diverse phases of patient care during the stay in the emergency department. In addition, a subset of about six ...

数据来源：ArXiv Domain LLM Domain Papers1. The Coin Flip Judge? Reliability and Bias in LLM-as-a-Judge EvaluationAbstract:LLM-as-a-Judge is now widely used to rank model outputs, train reward models, and populate public leaderboards, but its run-to-run reliability remains under-characterized. We study repeated identical evaluations on 29 tasks spanning 10 categories using two OpenAI judge models (GPT-4o-mini and GPT-4.1-mini), with 50 pairwise trials and 50 pointwise trials per question, supplement ...

数据来源：ArXiv Domain LLM Domain Papers1. Exposing the Unsaid: Visualizing Hidden LLM Bias through Stochastic Path AggregationAbstract:Large Language Models (LLMs) exhibit representational and syntactic biases that are difficult to evaluate due to the stochastic nature of text generation. Standard auditing methods rely on a single output inspection or static automated metrics. These approaches obscure the underlying probability distributions and fail to capture biases hidden in lower-probability g ...

数据来源：ArXiv Domain LLM Domain Papers1. Exposing the Unsaid: Visualizing Hidden LLM Bias through Stochastic Path AggregationAbstract:Large Language Models (LLMs) exhibit representational and syntactic biases that are difficult to evaluate due to the stochastic nature of text generation. Standard auditing methods rely on a single output inspection or static automated metrics. These approaches obscure the underlying probability distributions and fail to capture biases hidden in lower-probability g ...

数据来源：ArXiv Domain LLM Domain Papers1. Exposing the Unsaid: Visualizing Hidden LLM Bias through Stochastic Path AggregationAbstract:Large Language Models (LLMs) exhibit representational and syntactic biases that are difficult to evaluate due to the stochastic nature of text generation. Standard auditing methods rely on a single output inspection or static automated metrics. These approaches obscure the underlying probability distributions and fail to capture biases hidden in lower-probability g ...

数据来源：ArXiv Domain LLM Domain Papers1. HierBias: Context-Conditioned Hierarchical Media Bias Detection with Multi-Task Type ClassificationAbstract:Media bias detection is a critical task for ensuring fair and balanced information dissemination, yet existing sentence-level approaches classify each sentence independently, ignoring inter-sentence contextual signals that human annotators naturally exploit. We present \textbf{HierBias}, a hierarchical context-conditioned media bias detector that for ...

数据来源：ArXiv Domain LLM Domain Papers1. TokenScope: Token-Level Explainability and Interpretability for Code-Oriented Tasks in Large Language ModelsAbstract:Understanding how Large Language Models (LLMs) make token-level decisions during code generation remains a major challenge for both researchers and practitioners. While recent tools provide insights into model internals or generation outcomes, they often lack decoding-time signals, fine-grained uncertainty measures, and interactive mechanism ...