Hybrid Gated Attention
arXiv:2608.11805v1 Announce Type: new Abstract: Gated attention is an effective approach to mitigate attention sinks and enhance the representational capacity of attention. To further extend its effec
Knowledge catalogue
arXiv:2608.11805v1 Announce Type: new Abstract: Gated attention is an effective approach to mitigate attention sinks and enhance the representational capacity of attention. To further extend its effec
arXiv:2608.11354v1 Announce Type: new Abstract: Modern recommender systems treat observed actions as reliable proxies for user preferences, yet interactions often reflect exploration or comparison rat
arXiv:2608.11521v1 Announce Type: cross Abstract: World action models (WAMs) condition robot actions on predicted futures, but iterative video rollout increases deployment latency. We ask whether acti
arXiv:2608.11753v1 Announce Type: new Abstract: Financial text is produced and interpreted within a market environment, yet financial text classifiers almost always receive text alone. We study whethe
arXiv:2608.11498v1 Announce Type: new Abstract: Natural-language-based scenario generation offers an intuitive means of describing rare and complex driving interactions, yet it is still uncertain whet
arXiv:2608.12283v1 Announce Type: cross Abstract: Large language models can extract richer signals from financial news than fixed sentiment lexicons, and recent work has explored feeding such signals
arXiv:2608.11919v1 Announce Type: new Abstract: Training large language models on limited hardware is increasingly a scheduling problem across GPU compute, host memory, PCIe transfer, and storage band
arXiv:2608.12198v1 Announce Type: cross Abstract: Recent research in machine and deep learning has shown the potential of learningbased motion planning approaches to improve the driving behavior of au
arXiv:2603.20895v3 Announce Type: replace Abstract: Existing routers rely on semantic query features or handcrafted features, which often fail to capture model-specific failures or intrinsic task diff
arXiv:2508.12450v2 Announce Type: replace Abstract: This article presents an adaptive mean shift algorithm in which every parameter used at a point is derived from that point's own distance distributi
arXiv:2608.11417v1 Announce Type: new Abstract: Human movement is inherently variable, with variability structured according to task relevance: movements are typically more consistent at task-critical
arXiv:2608.11922v1 Announce Type: new Abstract: Predictive-distribution entropy makes a strong selection rule in retrieval-augmented question answering: across five QA benchmarks, keeping the candidat
arXiv:2608.12086v1 Announce Type: new Abstract: Vision-language models, such as contrastive language-image pre-training (CLIP)-based approaches, have reached state-of-the-art (SOTA) results in medical
arXiv:2608.11359v1 Announce Type: new Abstract: Electricity price forecasting is crucial for market participants but remains difficult because prices are volatile, market-specific, and closely tied to
arXiv:2606.13840v2 Announce Type: replace-cross Abstract: Autonomous driving is shifting from isolated vehicle intelligence toward multi-agent embodied systems that share perception, infer intent, and
arXiv:2608.11755v1 Announce Type: cross Abstract: Long-form song generation models continue to improve in duration, structural integrity, and acoustic complexity, making reliable aesthetic rewards inc
arXiv:2606.17598v2 Announce Type: replace-cross Abstract: Humans naturally leverage diverse sensing modalities to interact with the physical world, while most Vision-Language-Action (VLA) models for r
arXiv:2608.11352v1 Announce Type: new Abstract: Sign language translation has achieved strong results with Transformer architectures, yet recent improvements largely rely on scaling model capacity at
arXiv:2506.17332v2 Announce Type: replace-cross Abstract: By 2050, people aged 65 and over are projected to make up 16% of the global population. As aging is closely associated with increased fall ris
arXiv:2509.18751v4 Announce Type: replace Abstract: Recently reconstruction-based deep models have been widely used for time series anomaly detection, but as their capacity and generalization capabili
arXiv:2608.11769v1 Announce Type: new Abstract: Vision-language-action (VLA) policies are expected to operate robustly across variations in the robot's initial configuration, yet aggregate task succes
arXiv:2608.12018v1 Announce Type: new Abstract: Regional dialectal variation poses a fundamental challenge to natural language processing (NLP) in Bangla, where over 240 million speakers communicate a
arXiv:2608.12050v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) introduce explicit functional representations by parameterizing each network edge as a learnable univariate function.
arXiv:2608.11460v1 Announce Type: new Abstract: Large Language Model-powered agents are increasingly used in the workplace via human-artificial intelligence (AI) collaboration. In this new era of work
arXiv:2608.11830v1 Announce Type: cross Abstract: The deployment of large language models (LLMs) in mental health contexts raises questions about the relationship between clinical safety and environme
arXiv:2608.11572v1 Announce Type: new Abstract: Coarse-grid numerical solvers can substantially reduce the computational cost of time-dependent PDE simulation, but under-resolution often degrades both
arXiv:2608.12251v1 Announce Type: cross Abstract: Financial volatility is regime dependent, yet incorporating regime information into neural networks can also destabilize training. This paper asks whe
arXiv:2608.11239v1 Announce Type: cross Abstract: Administering Database Management Systems (DBMS) instances requires Database Administrators (DBA) to balance performance in terms of Service Level Agr
arXiv:2608.11573v1 Announce Type: cross Abstract: Achieving effective self-correction, where models verify and correct their own mistakes, remains a fundamental challenge for large language models (LL
arXiv:2603.20667v2 Announce Type: replace-cross Abstract: Existing prompt-optimization techniques rely on local signals, causing poor generalization across tasks. In addition, they also rely on weak u
arXiv:2608.11742v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a competitive alternative to autoregressive language models, offering the potential for substant
arXiv:2603.24060v3 Announce Type: replace Abstract: Despite the promise of Vision-Language-Action (VLA) models as generalist robotic controllers, their robustness against perceptual noise and environm
arXiv:2608.11541v1 Announce Type: new Abstract: Machine learning models should be robust, in the sense of remaining predictively consistent under permissible variations. A model's predictions should i
arXiv:2608.11669v1 Announce Type: cross Abstract: Reinforcement learning against rubrics, lists of criteria graded by an LLM judge, has become a standard way to post-train language models on tasks wit
arXiv:2608.12232v1 Announce Type: new Abstract: Geometry-aware video object scaling aims to anisotropically resize the object along object-centric axes while preserving geometric plausibility, tempora
arXiv:2608.12220v1 Announce Type: cross Abstract: Existing Vision-Language Models (VLMs) exhibits a critical bottleneck in robust spatial reasoning. Recent reinforcement learning (RL) methods aim to c
arXiv:2608.11292v1 Announce Type: new Abstract: Multimodal models increasingly reach for tools when solving visual tasks (crop, zoom, rotate, brighten), a paradigm known as thinking-with-images. The c
arXiv:2608.11350v1 Announce Type: new Abstract: Embodied agents are increasingly built as systems around foundation models, where performance depends not only on model weights but also on the skills,
arXiv:2608.11420v1 Announce Type: new Abstract: Medical diagnostic reasoning is a high-impact use case for LLMs that carries significant implications for the health and wellbeing of users. When OpenAI
arXiv:2608.12278v1 Announce Type: cross Abstract: Artificial intelligence tools for education and language support are increasingly framed as scalable responses to access gaps in under-resourced commu
arXiv:2608.11951v1 Announce Type: cross Abstract: Extreme events in air transport, such as severe arrival delays and abnormal air times, cause cascading network disruptions with substantial operationa
arXiv:2608.11243v1 Announce Type: new Abstract: We argue that a single structural fact organizes a wide range of phenomena in contemporary AI safety: a semantic safety constraint (e.g., the agent does
arXiv:2608.11407v1 Announce Type: new Abstract: Robust traffic simulators are crucial for developing and testing autonomous vehicles to reduce the costly, labor-intensive real-world data collection pr
arXiv:2604.07037v2 Announce Type: replace-cross Abstract: Accelerator-based neutrino physics is entering an energy-frontier regime in which interactions reach the TeV scale and produce exceptionally d
arXiv:2604.18064v2 Announce Type: replace Abstract: Human motion world models should capture motion's intentionality by being executable: adaptable to different actions and capable of assessing motion
arXiv:2608.11245v1 Announce Type: new Abstract: Online education offers unprecedented scalability and accessibility to global learners from diverse backgrounds, but it often suffers from low engagemen
arXiv:2608.11246v1 Announce Type: new Abstract: The success of coding agents has established the harness as a paradigm: what an agent achieves depends not on the model alone, but on the infrastructure
arXiv:2608.11829v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as a promising post-training technique for enhancing LLM reasoning. It is commonly believed to enable the stu
arXiv:2608.11785v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for financial analysis and trading, but direct trading remains challenging because the predicti
arXiv:2608.11223v1 Announce Type: cross Abstract: Entry-only automatic fare collection systems record boardings but not alightings, preventing direct construction of origin-destination (OD) matrices.
arXiv:2608.11860v1 Announce Type: cross Abstract: Data-driven inverse design enables efficient generation of nanophotonic structures with prescribed optical responses, but spectrum-to-geometry mapping
arXiv:2312.00114v3 Announce Type: replace Abstract: Event cameras are a novel type of biologically inspired vision sensor known for their high temporal resolution, high dynamic range, and low power co
arXiv:2604.03924v2 Announce Type: replace-cross Abstract: Goal-oriented conversational systems require making sequential decisions under uncertainty about the user's intent, where the algorithm must b
arXiv:2608.11280v1 Announce Type: cross Abstract: Skin cancer diagnosis from dermoscopic images remains challenging due to high intra-class variability, inter-class similarity, class imbalance, and th
arXiv:2603.08131v2 Announce Type: replace-cross Abstract: 3D Visual Grounding (3DVG) localizes objects from natural-language descriptions in 3D scenes and is fundamental to embodied AI applications. A
arXiv:2608.11840v1 Announce Type: cross Abstract: Growing demand for artificial intelligence (AI) inference services requires scalable infrastructure, yet centralized serving costs rise with demand. W
When enterprises transition from using simple chat assistants to autonomous, agentic workloads, they quickly run into a hard truth: Agents are prone to inaccurate insights when working with directly r
arXiv:2608.11251v1 Announce Type: cross Abstract: Fairness in AI systems has become more important with recent regulatory demands, such as the EU AI Act. Traditional approaches often do not take into
arXiv:2608.11435v1 Announce Type: new Abstract: Forward and inverse modeling of parametric dynamical systems requires surrogate models that are not only accurate for state prediction, but also informa
arXiv:2608.11592v1 Announce Type: new Abstract: Closed-track testing plays a fundamental role in the verification and validation of automated driving systems (ADS), particularly for safety-critical sc