Knowledge catalogue
arXiv:2610.11389v1 Announce Type: new Abstract: Neural Machine Translation (NMT) models, while capable of producing highly fluent outputs, remain vulnerable to hallucinations, which are translations t
arXiv:2610.11379v1 Announce Type: new Abstract: JEV models make multimodal decisions by directly scoring candidates. Although the common context is encoded once, candidate evaluation can still repeat
arXiv:2610.11459v1 Announce Type: cross Abstract: Outside the linear-Gaussian regime, conditional sampling from Gaussian processes (GPs) is challenging. Recent methods such as FlowGP (Moss et al., (20
arXiv:2610.11310v1 Announce Type: new Abstract: While 3D spatial reasoning in dynamic egocentric environments is crucial for embodied intelligence, audio-visual large language models (AV-LLMs) lack ex
arXiv:2610.11826v1 Announce Type: cross Abstract: Object hallucination remains a major obstacle for large vision-language models (LVLMs) to generate reliable content. An intuitive mitigation strategy
arXiv:2610.11770v1 Announce Type: new Abstract: AI-Native video creation is shifting from isolated video clips toward iterative video creation workflows. However, existing datasets remain largely vide
arXiv:2610.10959v1 Announce Type: new Abstract: In recent years, persistent homology has seen rapid adoption in deep learning, yet its computation remains a major bottleneck in network training. This
arXiv:2610.10633v1 Announce Type: cross Abstract: Screening in systematic reviews (SRs) is manual and time-consuming. Prior work has explored large language models (LLMs) for automating this step, but
arXiv:2610.11175v1 Announce Type: cross Abstract: Modern data-driven decision-making methods, such as imitation learning (IL) and reinforcement learning (RL), have achieved great success in solving ma
arXiv:2610.10919v1 Announce Type: cross Abstract: Despite decades of data quality (DQ) research, a gap remains between DQ dimensions, such as accuracy or completeness, which the literature defines in
arXiv:2610.11783v1 Announce Type: new Abstract: Shared e-scooter services have become a widely adopted urban transport mode. While most users ride responsibly, alcohol intoxication stands out among th
arXiv:2610.11953v1 Announce Type: new Abstract: Shapley values are among the most popular feature-attribution explanations. Efficient approaches for computing/estimating Shapley values for tree-based
arXiv:2610.11138v1 Announce Type: new Abstract: Inverse rendering decomposes an image into intrinsic properties such as appearance, illumination, geometry, and material, yet these properties are inher
arXiv:2610.10650v1 Announce Type: new Abstract: Work zones are critical yet hazardous components of transportation infrastructure, requiring carefully designed Transportation Management Plans (TMPs) t
arXiv:2610.10918v1 Announce Type: new Abstract: Large Language Models (LLMs) are considered to be a more efficient and cost-effective alternative to human judgment for Machine Translation (MT) evaluat
arXiv:2505.24282v2 Announce Type: replace Abstract: Language-driven action localization in videos requires not only semantic alignment between language query and video segment, but also prediction of
arXiv:2610.11264v1 Announce Type: new Abstract: Given the inherent unpredictability of packet loss in vehicular wireless communications, V2X collaborative perception can yield practical benefits only
arXiv:2610.12196v1 Announce Type: new Abstract: Autonomous racing requires accurate trajectory tracking near the handling limits of a vehicle while maintaining low computational latency. Geometric con
arXiv:2610.11573v1 Announce Type: new Abstract: The memory capabilities of Large Language Models (LLMs) have garnered increasing attention recently. Despite great success achieved, existing retrieval-
arXiv:2610.11989v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own generated responses using token-level teacher supervision. However, uniform weighting overlooks
arXiv:2610.10989v1 Announce Type: cross Abstract: Researchers are exploring effective one-step generative model continuously, and, Drifting Models (Deng et al., 2026), demonstrate great potential in o
arXiv:2610.11176v1 Announce Type: new Abstract: Multimodal remote sensing image registration is a crucial prerequisite for the collaborative processing and downstream application of remote sensing dat
arXiv:2610.12030v1 Announce Type: new Abstract: Large Language Models (LLMs) have renewed interest in autoformalization. Yet, when First-Order Logic (FOL) is considered as the target formalism, the fi
arXiv:2610.11313v1 Announce Type: new Abstract: A fundamental question in neural network architecture optimization is whether the minimum hidden-neuron count required to approximate a target function
arXiv:2610.11735v1 Announce Type: new Abstract: Onboard Artificial Intelligence can improve responsiveness and bandwidth efficiency of Earth Observation systems by processing data directly on the sate
arXiv:2512.13892v3 Announce Type: replace-cross Abstract: Reliable estimation of feature contributions in machine learning models is essential for transparency, algorithmic fairness, and regulatory co
arXiv:2610.11423v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student model by aligning its policy with a teacher model on trajectories generated by the student model itself. T
arXiv:2610.12410v1 Announce Type: cross Abstract: LLM developers post-train their models to exhibit prosocial values and behavioral traits, which are enumerated in an alignment target. However, while
arXiv:2610.11544v1 Announce Type: new Abstract: While predicting prosody from text is an established task in the field, the opposite direction, predicting text that fits a given prosodic pattern, rema
Hello all! Thank you to everyone that contributed their feedback and notes for LlamAmpere the last time I posted. I've continued to chip away at improvements for the 3090 crowd -- this release is mode
arXiv:2610.11358v1 Announce Type: new Abstract: Cross-model KV-cache reuse remains a key challenge in modern LLM serving. Coding agents and multi-model systems increasingly route a shared context acro
arXiv:2602.07878v2 Announce Type: replace-cross Abstract: LLM inference is inherently expensive, even a modest slowdown can translate into substantial operating costs and severe availability risks. Re
arXiv:2610.11416v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a prominent framework for complex robotic manipulation, building on the strong semantic understand
arXiv:2510.25257v2 Announce Type: replace Abstract: Real-time object detection has achieved substantial progress through meticulously designed architectures and optimization strategies. However, the p
arXiv:2606.18096v2 Announce Type: replace-cross Abstract: Structured State Space Models (SSMs), including the S4 and S4D architectures, have recently emerged as powerful alternatives to attention-base
arXiv:2610.11773v1 Announce Type: new Abstract: Guard models are increasingly used to safeguard LLM-based agents, primarily by identifying actions that agents are forbidden to perform. However, identi
arXiv:2610.11469v1 Announce Type: cross Abstract: Recent large vision-language models (VLMs) pair a visual encoder with a large language model (LLM) and perform well on diverse image-text tasks, yet t
arXiv:2610.11451v1 Announce Type: new Abstract: We introduce SAIL, an open model with 35B total and 3B active parameters for literature research, scientific coding, and multi-step research workflows.
arXiv:2610.11567v1 Announce Type: cross Abstract: Battery state of health (SoH) forecasting is important for battery management, but remains challenging due to nonlinear degradation and heterogeneity
arXiv:2610.10812v1 Announce Type: new Abstract: Small language models (SLMs) have been increasingly adopted for onboard robot operation because they enable intelligent decision-making. However, existi
arXiv:2610.11296v1 Announce Type: new Abstract: Implicit Neural Representations (INRs) have emerged as a compelling paradigm for modeling multidimensional signals by mapping continuous coordinates to
arXiv:2610.11366v1 Announce Type: new Abstract: Spatial coding agents significantly improve spatial reasoning in Multimodal Large Language Models (MLLMs) by using external tools to generate verified e
arXiv:2610.10807v1 Announce Type: new Abstract: Estimating the symbolic or analytical form of probability density functions (PDFs) from observed samples is a fundamental challenge in statistical and c
arXiv:2610.11241v1 Announce Type: new Abstract: Human body point clouds are a versatile representation for AI-enabled human sensing. However, existing methods using LiDAR, radar, and depth cameras suf
arXiv:2610.11216v1 Announce Type: cross Abstract: Diffusion and autoregression (AR) have long been seen as different categories of generative models, with diffusion specialising in continuous fields a
arXiv:2610.10924v1 Announce Type: cross Abstract: The Tensor-Memory Equilibrium (TME) model of 'FP8 is All You Need (Part 1)' calculates the execution time of Ozaki Scheme II emulation of fp64 as the
arXiv:2610.12276v1 Announce Type: new Abstract: Legged robots are promising candidates for future lunar surface missions because they can traverse steep, loose, and obstacle-rich terrain that challeng
arXiv:2610.11072v1 Announce Type: new Abstract: Autonomous navigation in cluttered and constrained environments typically assumes a fixed environment and searches only for paths within existing free s
arXiv:2610.10972v1 Announce Type: new Abstract: Assessing useful reuse in neural PDE solvers is challenging: final accuracy can reflect source learning and target-time computation. Our reuse contract
arXiv:2610.11037v1 Announce Type: new Abstract: Recent image editing systems have achieved impressive semantic understanding, visual fidelity, and instruction-following ability, while video editing re
TRL v1.15 is out, and it’s an absolute banger of a release for memory-efficient post-training. The main change: SFT, DPO, KTO, GRPO, RLOO and Distillation now use a fused LM head by default. Instead o
arXiv:2610.11764v1 Announce Type: new Abstract: Reliable crop-row perception is essential for autonomous agricultural robots, but low-cost deployment is constrained by computation, memory, power, and
arXiv:2610.12114v1 Announce Type: new Abstract: Knowledge distillation (KD) transfers knowledge from stronger Teacher models to weaker Student models, but most methods require training the Student par
arXiv:2610.12119v1 Announce Type: cross Abstract: Algorithm Selection is essential for efficient Constraint Programming. Over the years, many algorithm selectors based on machine learning methods have
arXiv:2610.11638v1 Announce Type: new Abstract: Evaluating user experience (UX) with automated computational methods has gained increasing attention, supported by empirical evidence from UXBench. Howe
arXiv:2610.11809v1 Announce Type: new Abstract: Robust navigation in cluttered environments remains a fundamental challenge for quadrotors, particularly when strong wind disturbances arise, which pert
arXiv:2610.10805v1 Announce Type: new Abstract: As AI systems increasingly interact with people and make decisions about them, understanding human interpretations becomes an important part of developi
arXiv:2610.09551v1 Announce Type: new Abstract: Background: Modern software systems increasingly rely on Machine Learning (ML) assets (i.e., pre-trained models, datasets, benchmarks) for building, eva
arXiv:2610.08985v1 Announce Type: cross Abstract: The aim of processing and analyzing experimental data from physical experiments is to obtain physically significant information about the phenomenon u
arXiv:2606.05335v2 Announce Type: replace Abstract: Theoretical studies of machine learning models commonly consider different limiting regimes in which the learning dynamics of gradient descent becom