Knowledge catalogue
arXiv:2608.28886v1 Announce Type: cross Abstract: What does a generation loop gain from learning on its own verified successes? In cycles of generate, verify, select and LoRA-consolidate on online bin
arXiv:2608.30975v1 Announce Type: cross Abstract: Cardiac magnetic resonance imaging (CMR) produces rich sequential data such as temporal cine videos and spatial LGE/mapping stacks, yet most deep lear
arXiv:2505.23862v2 Announce Type: replace-cross Abstract: The mRNA optimization is essential for mRNA vaccines, therapies, and industrial protein production. Based on current explorations, an ideal op
arXiv:2507.23129v2 Announce Type: replace-cross Abstract: We preseent an open-source image reconstruction package built upon PyTorch, enabling modern deep-learning reconstructions. It uses open data f
arXiv:2608.29477v1 Announce Type: cross Abstract: Document question-answering systems increasingly answer questions over collections of retrieved documents rather than one clean source, so robustness
arXiv:2608.28675v1 Announce Type: cross Abstract: Video reasoning tasks such as grounded video question answering and temporal grounding require selecting temporal evidence that supports the query. In
arXiv:2608.28674v1 Announce Type: new Abstract: Multi-exposure is an efficient way to capture real-world high-dynamic-range (HDR) scenes. However, HDR imaging suffers from severe ghosting artifacts in
arXiv:2608.28697v1 Announce Type: new Abstract: Additive manufacturing (AM) enables compact hydraulic components whose internal fluid channels can follow free-form 3D paths rather than conventionally
arXiv:2510.01159v3 Announce Type: replace Abstract: Learning the dynamics of a process given sampled observations at several time points is an important but difficult task in many scientific applicati
arXiv:2608.29186v1 Announce Type: new Abstract: Federated Video Domain Adaptation (FVDA) enables collaborative learning across distributed and non-IID video datasets while preserving privacy, but is u
arXiv:2608.28680v1 Announce Type: new Abstract: Informal settlements represent a major urban challenge in rapidly expanding cities, yet their identification from Earth Observation (EO) data remains di
arXiv:2608.29008v1 Announce Type: new Abstract: Accurate forecasting of grape berry temperature (Tb) is essential for enabling timely heat stress management in vineyards. In this study, a feed-forward
arXiv:2608.30997v1 Announce Type: new Abstract: Reflective smartphone cover glass is challenging to inspect from a single fixed viewpoint because defect visibility varies with viewing geometry and spe
arXiv:2608.30028v1 Announce Type: new Abstract: This paper introduces a family of multiclass linear Perceptron classifiers with a multiplicative margin mechanism (MMPerc), as an alternative to standar
arXiv:2608.30726v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) is a fundamental component of affective computing that aims to decipher complex emotional states by integrating verb
arXiv:2510.06113v2 Announce Type: replace Abstract: Survival analysis plays a vital role in making clinical decisions. However, the models currently in use are often difficult to interpret, which redu
arXiv:2503.00610v2 Announce Type: replace-cross Abstract: Understanding how people perceive urban environments is essential for inclusive planning, yet conventional surveys are costly and difficult to
arXiv:2608.31065v1 Announce Type: new Abstract: Surgical phase recognition is key to context-aware computer-assisted feedback in vitreoretinal procedures, yet the scarcity of synchronized multimodal i
arXiv:2608.30262v1 Announce Type: new Abstract: Scientific simulations generate collections of physical fields with heterogeneous statistics and dependencies, yet learned compressors often encode thos
arXiv:2608.30662v1 Announce Type: new Abstract: This paper presents Murano, an open source framework for designing, running, and reproducing mechanistic interpretability studies of large language mode
arXiv:2603.02482v2 Announce Type: replace-cross Abstract: Safety evaluation of multimodal large language models requires tracking not only whether an attack succeeds, but also how the interaction unfo
arXiv:2608.30940v1 Announce Type: cross Abstract: Generative music systems are increasingly presented as tools that democratize music creation, yet their practical suitability for musicians remains un
arXiv:2512.23667v3 Announce Type: replace Abstract: Intrinsic image decomposition aims to recover material and illumination factors from RGB observations, but real-world images entangle reflectance wi
arXiv:2608.28874v1 Announce Type: new Abstract: The automated sorting of shredded black plastics from end-of-life (EOF) industrial waste presents a significant challenge in recycling facilities, prima
arXiv:2608.29601v1 Announce Type: cross Abstract: We present N_0-Foundation, a paradigm for tactile-enabled embodied manipulation, which integrates tactile sensing hardware, large-scale multimodal dat
arXiv:2608.28933v1 Announce Type: new Abstract: Stereo reconstruction is one of the last remaining Computer Vision tasks where all state-of-the-art methods employ a heavy architectural inductive bias.
arXiv:2608.29540v1 Announce Type: new Abstract: This paper introduces NepScript Genesis, a Neural Architecture Search (NAS) framework for automated Generative Adversarial Network (GAN) discovery, appl
arXiv:2608.29074v1 Announce Type: new Abstract: We study online optimization with nested shrinking feasible regions in two settings: convex optimization with nested evolving feasible sets (CONES) and
arXiv:2509.12458v3 Announce Type: replace-cross Abstract: Miniaturized Uncrewed Aerial Vehicles (UAVs) can access indoor and hard-to-reach spaces, but severe constraints on payload and autonomy have l
arXiv:2608.29714v1 Announce Type: cross Abstract: Longitudinal cohort studies produce repeated data that enable the assessment of time-varying association patterns between exposures and health outcome
arXiv:2608.29331v1 Announce Type: new Abstract: Video traffic constitutes a significant share of global web traffic. To reduce its volume, video codecs have been developed and continuously improved. W
arXiv:2608.29112v1 Announce Type: new Abstract: Recent advances in anomaly detection (AD) for industrial inspection have pushed performance on standard benchmarks toward saturation. However, strong be
arXiv:2405.07392v4 Announce Type: replace-cross Abstract: Many existing visual SLAM methods can achieve high localization accuracy in dynamic environments by leveraging deep learning to mask moving ob
arXiv:2608.28608v1 Announce Type: cross Abstract: Ancient Indian medical texts like Sushruta Samhita have extensive information on diseases, treatments, and surgical techniques. Yet, their ancient for
arXiv:2608.29609v1 Announce Type: new Abstract: Semantic segmentation is a crucial task for understanding Mars, the most Earth-like planet in our solar system. However, it is challenging because the M
arXiv:2608.28875v1 Announce Type: cross Abstract: Supplying context at inference time to a large multimodal model is an inexpensive lever for adapting speech transcription to a domain, and earlier res
arXiv:2608.30417v1 Announce Type: new Abstract: We give a complete characterization of equivariant multi-head self-attention (MHSA): if an MHSA layer is equivariant to a symmetry group G, then G can o
arXiv:2608.30194v1 Announce Type: new Abstract: Diffusion models have recently advanced text-to-video (T2V) generation, yet they still struggle with fine-grained compositional alignment, such as attri
arXiv:2608.30944v1 Announce Type: new Abstract: In online retailing, when a product sells out, a retailer often sees only the units sold, not how many customers would have bought it had inventory been
arXiv:2608.31036v1 Announce Type: new Abstract: While low-rank adaptation (LoRA) is widely used for parameter-efficient model adaptation, how to regularize its training dynamics for stable and effecti
arXiv:2608.30738v1 Announce Type: new Abstract: Robust understanding of user input is a core requirement for voice assistants deployed in real-world environments. In practice, these systems encounter
arXiv:2608.29066v1 Announce Type: cross Abstract: Stance detection is crucial for understanding the underlying attitude of an expression towards a target. Conversational stance detection is a more cha
arXiv:2608.29589v1 Announce Type: new Abstract: Text-to-image (T2I) safety guardrails fail to generalize equitably to non-standard dialects. Evaluating 23,080 paired prompts across five English dialec
arXiv:2608.29136v1 Announce Type: cross Abstract: We ask whether a model protects a user in the same way when that user speaks rather than types. Using a single distress vignette---a physical injury o
arXiv:2601.15436v3 Announce Type: replace Abstract: We propose a novel perspective for probing LLM sycophancy in a direct and neutral way, mitigating various forms of uncontrolled bias, noise, or mani
arXiv:2608.29820v1 Announce Type: new Abstract: Ultrasound B-mode imaging commonly suffers from speckle noise and artifacts, requiring a delicate balance between contrast, resolution, and preservation
arXiv:2608.29045v1 Announce Type: new Abstract: Biclustering, or co-clustering, aims to discover coherent submatrices by grouping rows and columns of a data matrix simultaneously. This local two-dimen
arXiv:2608.29568v1 Announce Type: cross Abstract: Different attack methods follow different search trajectories, they succeed on different subsets of samples, whereas existing hard-label black-box tex
arXiv:2608.30423v1 Announce Type: cross Abstract: Splatting-based algorithms reconstruct photorealistic, real-time-renderable, and mesh-exportable 3D scenes from regular images, but they represent a s
arXiv:2608.30616v1 Announce Type: new Abstract: Pottery is a primary source for reconstructing the chronological and economic dimensions of past societies. Archaeologists often document ceramic finds
arXiv:2608.30678v1 Announce Type: new Abstract: Text-rich image understanding requires multimodal large language models (MLLMs) to organize OCR (Optical Character Recognition)-grounded evidence across
arXiv:2608.28944v1 Announce Type: new Abstract: Credit risk analysis in financial institutions traditionally requires analysts to manually write SQL queries, run statistical computations, and build vi
arXiv:2607.19313v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves reasoning in large language models. Yet, typical RLVR approaches fail on diffic
arXiv:2608.29904v1 Announce Type: new Abstract: Modern video generators routinely fail at physical dynamics: objects float, trajectories violate gravity, contacts vanish. Standard denoising and flow-m
arXiv:2608.28905v1 Announce Type: new Abstract: Generative recommenders increasingly emit semantic IDs (SIDs): each item is a short sequence of hierarchical discrete codes from a residual quantizer, d
arXiv:2603.23938v2 Announce Type: replace Abstract: Most testbeds for omni-modal models assess multimodal understanding via textual outputs, leaving it unclear whether these models can properly speak
arXiv:2502.20325v3 Announce Type: replace-cross Abstract: Multi-rotor aerial autonomous vehicles (MAVs, more widely known as 'drones') have been generating increased interest in recent years due to th
arXiv:2608.31120v1 Announce Type: new Abstract: The motivation for this paper is the investigation of the trade-offs implicit in probabilistic models used in machine learning. Models are often used to
arXiv:2608.30320v1 Announce Type: new Abstract: We describe the architecture and ablations of Qwen3.8-Flash-Next, a sparse mixture-of-experts model with 125B parameters, 6B activated per token, and ad
arXiv:2608.29913v1 Announce Type: new Abstract: TinyML includes the implementation of machine learning on devices with limited memory and computing resources. With the development of technology, AI sy