Knowledge catalogue
arXiv:2604.27929v1 Announce Type: new Abstract: With the widespread adoption of large language models (LLMs), understanding their personality representation mechanisms has become critical. As a novel
arXiv:2604.28011v1 Announce Type: new Abstract: Ultrasound interpretation requires both precise lesion localization and holistic clinical reasoning, yet existing methods typically excel at only one of
arXiv:2304.14352v2 Announce Type: replace-cross Abstract: Currently, there is a trend for the wider public to rely on LLMs for financial or legal consultation, medical and mental support (Chatterji et
arXiv:2604.27115v1 Announce Type: new Abstract: Neuron pruning is widely used to reduce the computational cost and parameter footprint of large language models, yet it remains unclear whether neurons
arXiv:2604.28036v1 Announce Type: new Abstract: Exponential families encompass the distributions central to modern machine learning -- softmax, Gaussians, and Boltzmann distributions -- and underlie t
arXiv:2601.06992v2 Announce Type: replace-cross Abstract: Financial question answering (QA) over long corporate filings requires evidence to satisfy strict constraints on entities, financial metrics,
arXiv:2506.07180v3 Announce Type: replace-cross Abstract: As video large language models (Video-LLMs) become increasingly integrated into real-world applications that demand grounded multimodal reason
arXiv:2604.27660v1 Announce Type: new Abstract: Many real-world tasks require language models (LMs) to reason over complex contexts that exceed their parametric knowledge. This calls for context learn
arXiv:2510.05192v2 Announce Type: replace-cross Abstract: When AI agents operating with access to sensitive information encounter a conflict between completing an assigned task and following rules or
arXiv:2604.28193v1 Announce Type: new Abstract: Reconstructing 3D scenes from sparse, unposed images remains challenging under real-world conditions with varying illumination and transient occlusions.
arXiv:2604.27918v1 Announce Type: new Abstract: Existing talking avatar methods typically adopt an image-to-video pipeline conditioned on a static reference image within the same scene as the target g
arXiv:2503.01817v2 Announce Type: replace Abstract: A fundamental challenge in neurosymbolic systems is applying continuous gradient-based optimization to discrete logical domains. While fuzzy relaxat
arXiv:2601.10702v2 Announce Type: replace-cross Abstract: Deploying large language models in long-horizon, goal-oriented interactions remains challenging because similar entities and facts recur under
arXiv:2604.27351v1 Announce Type: new Abstract: Agentic large language model systems have demonstrated strong capabilities. However, their reliance on language as the universal interface fundamentally
arXiv:2604.27147v1 Announce Type: cross Abstract: In generative modeling, we often wish to produce samples that maximize a user-specified reward such as aesthetic quality or alignment with human prefe
arXiv:2604.27540v1 Announce Type: new Abstract: Scientific reasoning rarely stops at what is directly observable; it often requires uncovering hidden structure from data. From estimating reaction cons
arXiv:2604.28158v1 Announce Type: new Abstract: Existing research infrastructure is fundamentally document-centric, providing citation links between papers but lacking explicit representations of meth
arXiv:2604.27713v1 Announce Type: new Abstract: The risks posed by AI features are increasing as they are rapidly integrated into software applications. In response, regulations and standards for safe
arXiv:2604.25711v2 Announce Type: replace-cross Abstract: Source code and its accompanying comments are complementary yet naturally aligned modalities-code encodes structural logic while comments capt
arXiv:2604.27759v1 Announce Type: cross Abstract: Integrating domain knowledge into deep neural networks is a promising way to improve generalization. Existing methods either encode prior knowledge in
arXiv:2604.27128v1 Announce Type: cross Abstract: Foundation-model pipelines for individual-level livestock monitoring -- combining open-vocabulary detection, promptable video segmentation, and self-s
arXiv:2604.27742v1 Announce Type: new Abstract: The choice of loss function in classification involves a fundamental trade-off: smooth losses (like Cross-Entropy) enable fast optimization rates but yi
arXiv:2604.27345v1 Announce Type: new Abstract: Human annotators frequently disagree on emotion labels, yet most evaluations of Large Language Model (LLM) emotion annotation collapse these judgments i
arXiv:2604.27297v1 Announce Type: new Abstract: Deriving governing equations from empirical observations is a longstanding challenge in science. Although artificial intelligence (AI) has demonstrated
arXiv:2604.28167v1 Announce Type: cross Abstract: In this study, we use machine learning to classify and interpolate the phase structure of the Vicsek flocking model across the three-dimensional param
arXiv:2604.27300v1 Announce Type: new Abstract: Metamaterial discovery seeks microstructured materials whose geometry induces targeted mechanical behavior. Existing inverse-design methods can efficien
arXiv:2604.27393v1 Announce Type: new Abstract: Recent progress in multimodal large language models (MLLMs) has brought AI capabilities from static offline data processing to real-time streaming inter
arXiv:2603.21016v2 Announce Type: replace-cross Abstract: Large language models (LLMs) used for multiple-choice and pairwise evaluation tasks often exhibit selection bias due to non-semantic factors l
arXiv:2604.28130v1 Announce Type: new Abstract: Recent methods for arbitrary-skeleton motion capture from monocular video follow a factorized pipeline, where a Video-to-Pose network predicts joint pos
arXiv:2604.28107v1 Announce Type: new Abstract: Accurate state estimation of nonlinear dynamical systems is fundamental to modern aerospace operations across air, sea, and space domains. Online tracki
📢 Official Announcement: Qwen Partners with Fireworks AI to Accelerate Access to Qwen Family Models We are pleased to announce a strategic partnership between Qwen and Fireworks AI to deliver optimize
arXiv:2604.27201v1 Announce Type: cross Abstract: Hybrid-thinking language models expose explicit think and no-think modes, but current designs do not separate them cleanly. Even in no-think mode, mod
arXiv:2604.28169v1 Announce Type: cross Abstract: Modern video diffusion models excel at appearance synthesis but still struggle with physical consistency: objects drift, collisions lack realistic reb
arXiv:2604.27280v1 Announce Type: new Abstract: Nonstationary Gaussian processes (GPs) are essential for modeling complex, locally heterogeneous spatial data. A common modeling approach is the spatial
arXiv:2604.27379v1 Announce Type: new Abstract: Dialogue models are inherently reactive, responding to the current user turn without anticipating upcoming intents, which leads to redundant interaction
arXiv:2604.27319v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable progress in recent years, driving their adoption across a wide range of domains, including compu
arXiv:2604.28028v1 Announce Type: cross Abstract: Large language models (LLMs) have revolutionized Text-to-SQL generation, allowing users to query structured data using natural language with growing e
arXiv:2604.27553v1 Announce Type: new Abstract: When the visual style of text is considered, a wide variety can be observed in font, color, and size. However, when a word is read, its meaning is indep
arXiv:2604.27617v1 Announce Type: cross Abstract: With the widespread application of Unmanned Aerial Vehicles (UAVs) in bridge structural health monitoring, deep learning-based automatic crack detecti
arXiv:2604.28161v1 Announce Type: new Abstract: The robotic manipulation of Deformable Linear Objects (DLOs) is a fundamental challenge due to the high-dimensional, non-linear dynamics of flexible str
arXiv:2604.26985v1 Announce Type: cross Abstract: Masked diffusion models (MDMs) generate discrete sequences by iterative denoising under an absorbing masking process. In standard masked diffusion, if
arXiv:2604.27620v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) aims to enable an embodied agent to follow natural-language instructions and navigate to a target location in unsee
arXiv:2604.27574v1 Announce Type: cross Abstract: Channel fingerprint (CF) is considered a key enabler for facilitating the acquisition of channel state information (CSI) in massive multiple-input mul
arXiv:2604.27151v1 Announce Type: new Abstract: Computer-use agents provide a promising path toward general software automation because they can interact directly with arbitrary graphical user interfa
arXiv:2604.28179v1 Announce Type: new Abstract: Bronchoscopic navigation relies on registering endoscopic video to a preoperative CT scan, but respiratory motion deforms the airway by 5-20 mm, creatin
arXiv:2604.27232v1 Announce Type: new Abstract: Models of sign language have historically lagged behind those for spoken language (text and speech). Recent work has greatly improved their performance
arXiv:2501.12632v2 Announce Type: replace Abstract: Weakly supervised object localization (WSOL) models are trained using only image-level class labels. They can predict both the object class and spat
arXiv:2509.05753v2 Announce Type: replace-cross Abstract: The rise of synthetic media has blurred the boundary between reality and fabrication under the evolving power of artificial intelligence, fuel
arXiv:2604.28076v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced Table Question Answering, where most queries can be answered by extracting information or simple aggregatio
arXiv:2604.27499v1 Announce Type: new Abstract: Off-road nighttime autonomous driving suffers from unreliable visible-light perception, making infrared modality crucial for accurate freespace detectio
arXiv:2509.25845v3 Announce Type: replace-cross Abstract: Recent advancements in diffusion and flow-matching models have demonstrated remarkable capabilities in high-fidelity image synthesis. A promin
arXiv:2604.27928v1 Announce Type: cross Abstract: Tunnel inspection requires outputs that can support defect localization, measurement, severity grading, and engineering documentation. Existing traini
arXiv:2504.18902v2 Announce Type: replace-cross Abstract: In the forthcoming era of 6G networks, characterized by unprecedented data rates, ultra-low latency, and ubiquitous connectivity, effective ma
arXiv:2602.23163v3 Announce Type: replace Abstract: Large language models are beginning to show steganographic capabilities. Such capabilities could allow misaligned models to evade oversight mechanis
arXiv:2604.26319v1 Announce Type: new Abstract: Stance detection identifies the attitude of a text author toward a given target. Recent studies have explored various LLM-based strategies for this task
arXiv:2603.16496v2 Announce Type: replace Abstract: Large language model (LLM) agents increasingly rely on external memory to support long-horizon interaction, personalized assistance, and multi-step
Together AI announced a strategic partnership with Adaption to advance AI capabilities and deployment. The collaboration likely focuses on integrating Adaption's technology or services with Together A
arXiv:2603.13589v2 Announce Type: replace-cross Abstract: Estimating motion from spatiotemporal geoscientific data is a fundamental component of many environmental modeling and forecasting tasks. In t
The search did not return specific details about release b8982. Based on the llama.cpp project context from the search results, b8982 is a build/release version from the llama.cpp repository that foll
Based on the available search results, I cannot locate specific details about the b8989 release. However, b8989 is a commit hash from the llama.cpp repository releases. llama.cpp is a C/C++ implementa