Search: “banking”

arXiv:2608.28078v1 Announce Type: new Abstract: Vision foundation backbones provide strong representations for dense prediction, yet a single shared feature still needs to support tasks with different

arXiv:2608.26848v1 Announce Type: cross Abstract: Medical Visual Question Answering (Med-VQA) holds significant promise for clinical decision support, yet faces challenges due to limited annotated dat

arXiv:2608.26142v1 Announce Type: cross Abstract: Referring Expression Segmentation (RES) aims to generate pixel-wise segmentation masks from complex and implicit textual queries. While recent advance

arXiv:2608.25088v1 Announce Type: new Abstract: Cortical computation is strikingly low-dimensional: a handful of latent variables, carried in a neural population's activity, steer the higher-dimension

arXiv:2608.23397v1 Announce Type: new Abstract: Interactive clinical agents must gather decisive evidence and convert it into grounded actions under partial observability. A correct final diagnosis al

arXiv:2608.23411v1 Announce Type: new Abstract: LLM value studies often merge questionnaire ratings, pairwise choices, and values inferred from generated text into one profile. That merge assumes that

arXiv:2608.20447v1 Announce Type: new Abstract: Feature selection is a highly relevant task in a data-driven knowledge discovery project. Several techniques have been developed aiming at finding the f

arXiv:2603.01493v2 Announce Type: replace-cross Abstract: Personal photo albums are not merely collections of static images but living, ecological archives defined by temporal continuity, social entan

arXiv:2608.19888v1 Announce Type: cross Abstract: Streaming systems that maintain a pool of expert models must repeatedly decide whether to reuse an existing expert for arriving data, spawn a new one,

arXiv:2608.20295v1 Announce Type: new Abstract: Sparse pursuit after dictionary learning can yield a precise atom support even when its physical interpretation is not justified by the calibration data

arXiv:2608.19885v1 Announce Type: cross Abstract: Streaming systems that maintain a pool of expert models must repeatedly decide whether to reuse an existing expert for arriving data, spawn a new one,

arXiv:2608.18534v1 Announce Type: new Abstract: Large language models are increasingly used to support financial operations, but their apparent reasoning performance can depend on whether they receive

arXiv:2608.16211v1 Announce Type: new Abstract: Long-horizon agents are beginning to automate complete workflows that produce code, reports, and research artifacts. Medical imaging workflows are multi

arXiv:2608.14702v1 Announce Type: new Abstract: Film emulation reproduces the look of an analog film stock on a new digital photograph. We target its open-set form -- matching any reference film frame

arXiv:2608.16097v1 Announce Type: new Abstract: Graph neural networks are commonly described through family-specific equations whose notation obscures shared computations and structural differences. W

arXiv:2608.13722v1 Announce Type: new Abstract: This paper describes the University of Florida Gators submission to the WMT26 Low-Resource Indic Language Translation shared task. We adapt the retrieva

arXiv:2608.13980v1 Announce Type: new Abstract: Reasoning segmentation requires multimodal large language models (MLLMs) to translate implicit instructions into precise pixel-level masks. MLLMs encode

arXiv:2608.10743v1 Announce Type: new Abstract: Recent research empowers Large Language Models (LLMs) as multi-turn search agents to iteratively retrieve and generate outputs until complex tasks are s

arXiv:2608.10949v1 Announce Type: cross Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to preserve relevant evidence from continuously evolving streams under

arXiv:2608.08815v1 Announce Type: new Abstract: Traffic sign recognition (TSR) models based on deep neural networks achieve strong clean-data performance but remain vulnerable to physically realizable

arXiv:2608.07712v1 Announce Type: cross Abstract: A predictive model receives a self-supervised signal whenever the consequence of an action is observed. Using that signal after deployment is difficul

arXiv:2608.08290v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) repurposes a pretrained CLIP encoder for dense prediction without additional labeled supervision. Existing

arXiv:2608.05970v1 Announce Type: cross Abstract: Embodied visuomotor models, including Diffusion Policy (DP) and Vision-Language-Action (VLA) models, have demonstrated promising performance on roboti

arXiv:2608.03204v1 Announce Type: cross Abstract: Post-training reinforcement learning (RL) algorithms are commonly used to align large vision-language models (LVLMs) with human intent and the require

arXiv:2608.04009v1 Announce Type: new Abstract: Large language models (LLMs), and the agents built on top of them, are now benchmarked heavily on whether they can finish a task -- fix a bug, drive a b

arXiv:2608.02664v1 Announce Type: cross Abstract: Deploying ML models in regulated decision-making (credit underwriting, fraud detection, loan approval) requires demonstrating fairness and robustness

arXiv:2601.15307v2 Announce Type: replace-cross Abstract: The rapid development of automated survey generation technology has made it increasingly important to establish a comprehensive benchmark to e

arXiv:2607.29468v1 Announce Type: new Abstract: Self-play agents can generate training problems without questions from target benchmarks, but their curricula lack persistent state: failures affect gra

arXiv:2607.25169v1 Announce Type: cross Abstract: Message-passing graph neural networks are bounded by the 1-WL test and can miss topological structure that distinguishes non-isomorphic graphs. Positi

arXiv:2607.24589v1 Announce Type: new Abstract: The development of the Innovative Ecosystem (IE) presents a new paradigm for economic integration, collaborative advancement, and shared achievements. T

arXiv:2601.01856v3 Announce Type: replace Abstract: Feature-based anomaly detection is widely adopted in industrial inspection due to the strong representational power of large pre-trained vision enco

arXiv:2505.17492v2 Announce Type: replace Abstract: Project duplication detection is critical for project quality assessment because it helps avoid investment in repeated proposals. Existing methods u

arXiv:2607.24098v1 Announce Type: new Abstract: Referring video object segmentation (RVOS) requires segmenting a target specified by natural language throughout a video. Recent agentic approaches comb

arXiv:2607.23492v1 Announce Type: new Abstract: Concept erasure techniques (CETs) edit text-to-image diffusion models to erase undesired targets such as NSFW content or copyrighted styles, while prese

arXiv:2607.18451v1 Announce Type: cross Abstract: Frozen encoders are chosen by how well a lightweight head reads a finding from their features, not whether the geometry separates it. Nearest-neighbor

arXiv:2607.12358v1 Announce Type: new Abstract: Video diffusion models produce high-quality generations but remain slow at inference due to their sequential denoising procedure. Caching-based accelera

arXiv:2511.04689v3 Announce Type: replace-cross Abstract: Evaluating large language models (LLMs) typically requires thousands of benchmark items, making the process expensive, slow, and increasingly

arXiv:2607.12310v1 Announce Type: cross Abstract: While modern question answering (QA) systems excel on clean, schema-aligned corpora, real-world knowledge is rarely so neatly packaged. Answering ques

arXiv:2607.08392v1 Announce Type: cross Abstract: Amortized neural inverse design typically remains closed-world: component choices are fixed vocabulary tokens, coordinate grids are frozen at training

arXiv:2607.08716v1 Announce Type: new Abstract: In long-horizon tasks, decision-relevant state is often scattered across an expanding trajectory, while the action agent must surface it and act. As tra

arXiv:2607.04103v1 Announce Type: cross Abstract: The release of SR 26-2 marks a significant modernization of U.S. model risk management by replacing SR 11-7 with a more risk-based and materiality-sen

arXiv:2607.04894v1 Announce Type: new Abstract: Memory-based anomaly detection is attractive because it localizes defects from normal images without training a decoder or synthesizing pseudo anomalies

arXiv:2607.02072v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in domains requiring guardrails to detect unsafe, off-topic, or adversarial prompts. Existing g

arXiv:2607.00499v1 Announce Type: new Abstract: Automated pathology report generation from Whole Slide Images (WSIs) has attracted increasing attention in digital pathology. However, existing methods

arXiv:2606.27677v1 Announce Type: cross Abstract: World-action models have shown promising robot-manipulation performance by jointly predicting future visual states and actions. However, existing meth

arXiv:2606.24956v1 Announce Type: new Abstract: Spectral graph neural networks (GNNs) interpret message passing as frequency-selective filtering. While low-order spectral filters are efficient, their