Knowledge catalogue
arXiv:2508.04064v2 Announce Type: replace-cross Abstract: Horizontal federated learning (HFL) backdoor audits often summarize model behavior through clean accuracy (CA), mean attack success rate (ASR)
arXiv:2607.00535v1 Announce Type: cross Abstract: Few-step flow-map generators, such as consistency models and MeanFlow, accelerate sampling by directly learning long-range transport maps between nois
arXiv:2507.02961v2 Announce Type: replace-cross Abstract: Modern transportation network modeling increasingly involves the integration of diverse methodologies including sensor-based forecasting, rein
arXiv:2607.00763v1 Announce Type: cross Abstract: Digital forensic investigations of network intrusions require analytical outputs that are traceable, reproducible, and court-defensible - requirements
arXiv:2607.00745v1 Announce Type: new Abstract: Accurate fetal birth weight (FBW) estimation shortly before delivery is clinically valuable yet challenging due to its reliance on operator expertise, p
arXiv:2607.00591v1 Announce Type: new Abstract: With the increasing deployment of heterogeneous robot fleets in industrial environments, efficient coordination remains a critical challenge. Real-time
arXiv:2508.18224v3 Announce Type: replace-cross Abstract: Recent advances in sparse attention mechanisms have demonstrated strong potential for reducing the computational cost of long-context training
arXiv:2607.00595v1 Announce Type: new Abstract: Gaussian Splatting has achieved significant improvements by incorporating warping-based techniques. However, such methods suffer from pixel-level inaccu
arXiv:2607.00959v1 Announce Type: new Abstract: Audio-driven talking head synthesis has achieved impressive progress in lip synchronization and visual quality, yet generating expressive emotional avat
arXiv:2405.03650v4 Announce Type: replace Abstract: We study Generated Contents Enrichment (GCE), a conditional image-generation task in which a sparse scene description is first enriched through an e
arXiv:2607.00691v1 Announce Type: new Abstract: Black-box optimization is a fundamental science and engineering tool that makes it possible to optimize objectives without gradient information. Unfortu
arXiv:2512.09112v3 Announce Type: replace Abstract: Recent progress in text-to-video generation has achieved remarkable realism, yet fine-grained control over camera motion and orientation remains elu
arXiv:2603.20467v2 Announce Type: replace-cross Abstract: Stochastic differential equations (SDEs), which serve as the governing equations for dynamical systems in a broad range of applications, can b
arXiv:2511.14642v2 Announce Type: replace Abstract: Like visual processing, language processing is susceptible to illusions in which people systematically misperceive stimuli. In one such case--the co
arXiv:2607.01089v1 Announce Type: cross Abstract: Active learning reduces labeling cost by querying the most informative unlabeled samples, but standard coreset methods ignore known data symmetries an
arXiv:2607.00221v1 Announce Type: cross Abstract: We study the symmetric bouncing of a point robot within orthogonally-joined rectangles with equal width, which we refer to as pipes. We provide an exh
arXiv:2607.00143v1 Announce Type: cross Abstract: Online hate speech has been linked to a global rise in violence against minorities, including incidents such as mass shootings, lynchings, and ethnic
Hermes now supports reference-image editing functionality that allows users to input a source image along with up to 16 reference images for transformation, accessible through Codex/ChatGPT login cred
arXiv:2407.10887v4 Announce Type: replace-cross Abstract: Growing concerns over the theft and misuse of Large Language Models (LLMs) underscore the need for effective fingerprinting to link a model to
arXiv:2607.00494v1 Announce Type: new Abstract: Multi-animal tracking (MAT) is critical for wildlife monitoring and behavioral analysis, yet remains challenging due to uniform appearance, high density
arXiv:2607.01176v1 Announce Type: new Abstract: Magnetic resonance imaging (MRI) reconstruction under realistic acquisition conditions can be fundamentally viewed as estimating the underlying k-space
arXiv:2601.17020v2 Announce Type: replace-cross Abstract: With the rising popularity of interdisciplinary work and increasing institutional incentives in this direction, there is a growing need to und
arXiv:2607.00473v1 Announce Type: new Abstract: How many days of early behavior suffice for subscription churn prediction? In the public KKBox dataset, the early indicator of churn is typically an ind
arXiv:2607.00873v1 Announce Type: new Abstract: Rhetorical strategies and their influence on audiences are often studied through social media posts and comments. However, this focus overlooks the univ
arXiv:2607.01025v1 Announce Type: cross Abstract: Radio-frequency (RF) sensing is a central modality for counter-unmanned-aerial-system (counter-UAS) defence because it exploits the control, telemetry
arXiv:2607.01067v1 Announce Type: cross Abstract: As an essential modality for dexterous and contact-rich tasks, tactile sensing provides precise force feedback that cannot be reliably inferred from v
I’m looking to hire a Program Manager to help manage Sakana AI’s fast growing Recursive Self-Improvement (RSI) Lab 🚀 RSI Lab (English): https://sakana.ai/rsi-lab/ RSI Lab (日本語): https://sakana.ai/rsi-
arXiv:2607.01008v1 Announce Type: cross Abstract: Short-horizon prediction is essential for electro-optical UAV tracking, especially when the target is small, maneuvering, or intermittently observed.
arXiv:2607.01222v1 Announce Type: new Abstract: Recent 3D generative models can synthesize high-quality geometry but often struggle to reproduce intricate textures from reference images, largely due t
arXiv:2502.18975v2 Announce Type: replace Abstract: Machine learning models are inherently bound to the distribution of the training data, often exploiting non-causal shortcuts. As a result, achieving
arXiv:2607.00145v1 Announce Type: new Abstract: Inertial navigation systems aided by three-dimensional landmark measurements constitute a fundamental problem in robotic perception and state estimation
arXiv:2607.00058v1 Announce Type: new Abstract: Image quality is critical for accurate medical diagnosis. However, MRI, CT, and ultrasound images are often of low resolution and quality due to cost co
arXiv:2607.00329v1 Announce Type: cross Abstract: Recursive Feature Machines (RFMs) are a class of kernel machines that utilize the Average Gradient Outer Product (AGOP) as a mechanism for feature lea
arXiv:2607.00482v1 Announce Type: new Abstract: Reasoning language models frequently overthink: generating extended chains of behaviors such as hedging, approach abandonment, and self contradiction th
arXiv:2607.01000v1 Announce Type: new Abstract: Recent research has increasingly focused on understanding how Transformers store and process knowledge, as well as how this knowledge can be edited. Res
arXiv:2607.01225v1 Announce Type: cross Abstract: Prior work on imitation learning from suboptimal demonstrations typically relies on compressed supervision signals such as confidence estimates, discr
Large language models can exhibit emergent reasoning behaviors, often manifested as recurring lexical patterns (e.g., “wait,” indicating verification). However, complex reasoning trajectories remain s
arXiv:2607.00374v1 Announce Type: cross Abstract: Composed Image Retrieval (CIR) retrieves a target image from a reference image and a textual modification. While supervised CIR relies on costly tripl
Diffusion (Large) Language Models (dLLMs) now match the downstream performance of their autoregressive counterparts on many tasks, while holding the promise of being more efficient during inference. O
arXiv:2607.00228v1 Announce Type: cross Abstract: Modern time-domain surveys such as the Zwicky Transient Facility (ZTF) generate hundreds of thousands of alerts each night, making real-time decisions
arXiv:2607.00784v1 Announce Type: cross Abstract: Vision-language pretraining remains dominated by contrastive objectives, whereas vision-only self-supervised learning has largely adopted non-contrast
arXiv:2607.00634v1 Announce Type: cross Abstract: In settings such as fine-tuning and reinforcement learning, neural networks are often adapted under distribution shift. Standard adaptation methods ty
arXiv:2607.00588v1 Announce Type: new Abstract: Continuous diffusion language models such as ELF report record-low generative perplexity (Gen-PPL). We find a catch: these models repeat far more than h
arXiv:2607.00815v1 Announce Type: cross Abstract: SAT solvers settle combinatorial problems beyond the reach of interactive theorem provers and produce LRAT certificates for independent verification.
arXiv:2602.05275v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown immense promise in universal multimodal retrieval, which aims to find relevant items of various
arXiv:2607.01233v1 Announce Type: cross Abstract: LLMs are increasingly used to brainstorm research ideas, but existing evaluations mostly judge individual ideas by novelty, feasibility, or expert pre
arXiv:2607.00029v1 Announce Type: cross Abstract: Non-terrestrial networks (NTN) provide ubiquitous connectivity for embodied intelligence (EI), enabling robots in wilderness to leverage cloud resourc
Understanding how transformer components operate in LLMs is important, as it is at the core of recent technological advances in artificial intelligence. In this work, we revisit the challenges associa
arXiv:2607.01077v1 Announce Type: new Abstract: While inference-time scaling has improved the reasoning abilities of large language models (LLMs), the need to generate long chains-of-thought (CoTs) is
arXiv:2607.00848v1 Announce Type: new Abstract: In this opinion paper, we propose MetaHOPE, an error severity-aware annotation framework for evaluating metaphor translations. Metaphors present challen
arXiv:2607.00902v1 Announce Type: new Abstract: Driven by Artificial Intelligence-Generated Content (AIGC), the authenticity of audio-visual content is facing severe challenges. Temporal Forgery Local
arXiv:2607.00138v1 Announce Type: new Abstract: MG-SpaIR is a training-data-free framework for restoring a clean image from a single observation corrupted by a mixture of blur, downsampling, noise, an
arXiv:2603.22055v2 Announce Type: replace-cross Abstract: Underground mining robots are increasingly modeled for planning, operator training, and digital-twin workflows, where reliable actuator-level
arXiv:2601.11641v3 Announce Type: replace Abstract: While Diffusion Transformers (DiTs) have achieved notable progress in video generation, this long-sequence generation task remains constrained by th
arXiv:2604.01654v2 Announce Type: replace-cross Abstract: Recent advances in video generation have made AI-synthesized content increasingly difficult to distinguish from real footage. We propose a phy
arXiv:2511.19326v2 Announce Type: replace Abstract: Reconstructing biomechanically realistic 3D human motion - recovering both kinematics (motion) and kinetics (forces) - is a critical challenge. Whil
arXiv:2505.20857v2 Announce Type: replace Abstract: Motion retargeting for specific robot from existing motion datasets is one critical step in transferring motion patterns from human behaviors to and
arXiv:2607.00273v1 Announce Type: new Abstract: The core challenge in multi-view pedestrian detection (MVPD) lies in effective aggregation of visual features from different viewpoints for robust occlu
arXiv:2607.01185v1 Announce Type: new Abstract: Combinatorial optimization (CO) problems are difficult because certifiable discrete structure induces exponential search. One needs to search over the s
arXiv:2607.00529v1 Announce Type: new Abstract: Classic 3D scene graph generation approaches fail to work in real-time due to the heavy computational cost of environment mapping and the need to genera