Knowledge catalogue
arXiv:2512.20063v3 Announce Type: replace Abstract: We introduce exttt{PairFlow}, a lightweight preprocessing step for training Discrete Flow Models (DFMs) to achieve few-step sampling without requiri
arXiv:2605.24154v1 Announce Type: new Abstract: Current safety alignment of foundation models largely follows a one-size-fits-all paradigm, applying the same refusal policy across users and contexts.
arXiv:2605.24549v1 Announce Type: new Abstract: Efficiently updating Large Language Models (LLMs) with new or evolving factual knowledge remains a central challenge, as even parameter-efficient adapta
arXiv:2605.24785v1 Announce Type: new Abstract: Recent advances in multimodal web agents often rely on increased inference-time computation, including rollout search, verifier passes, offline skill di
arXiv:2605.25346v1 Announce Type: cross Abstract: Neural network (NN) dynamics models and control policies achieve strong performance in robotics, but providing sound guarantees under uncertainty rema
arXiv:2605.25348v1 Announce Type: cross Abstract: Low-dose computed tomography (LDCT) reconstruction faces a critical tradeoff between reconstruction quality and resource requirements. While recent de
arXiv:2605.23984v1 Announce Type: cross Abstract: Industrial anomaly detection has attracted significant attention as a fundamental challenge in industrial systems. The rapid advancement of heterogene
arXiv:2605.24792v1 Announce Type: cross Abstract: The major limitations of gastrointestinal (GI) endoscopy AI systems arise from a shortage of annotated data, strict privacy policies, and significant
arXiv:2605.26064v1 Announce Type: cross Abstract: We present Paris 2.0, the first video generation model pre-trained through decentralized computation. Its training recipe builds upon Paris 1.0 (arXiv
arXiv:2605.25029v1 Announce Type: new Abstract: Autonomous parking demands precise low-speed maneuvering within narrow, cluttered, and highly constrained environments, where vehicles must navigate tig
arXiv:2605.25782v1 Announce Type: new Abstract: Humanoid parkour requires locomotion policies to coordinate whole-body dynamics across rapidly changing terrains such as stairs, gaps, slopes, and obsta
arXiv:2602.00511v2 Announce Type: replace Abstract: Despite their empirical success, neural network classifiers remain difficult to interpret. In softmax-based models, class regions are defined implic
arXiv:2605.24352v1 Announce Type: new Abstract: Multi-agent collaboration, especially in human-AI teaming, requires agents that can adapt to novel partners with diverse and dynamic behaviors. Conventi
arXiv:2605.10977v2 Announce Type: replace-cross Abstract: Watermarking for large language models (LLMs) is a promising approach for detecting LLM-generated text and enabling responsible deployment. Ho
arXiv:2605.24731v1 Announce Type: cross Abstract: This paper presents a novel passivity-based semi-autonomous attitude control framework, with a particular focus on attitude kinematics defined on the
arXiv:2605.25401v1 Announce Type: new Abstract: Biomimetic autonomous underwater vehicle (BAUV) with multi-link mechanism is widely used in aquatic life observation and environmental surveys due to it
arXiv:2603.09943v2 Announce Type: replace Abstract: Computational pathology demands both visual pattern recognition and dynamic integration of structured domain knowledge, including taxonomy, grading
arXiv:2601.20539v3 Announce Type: replace Abstract: Large Language Models (LLMs) have enabled automated heuristic design (AHD) for combinatorial optimization problems (COPs), but existing frameworks'
arXiv:2502.10906v2 Announce Type: replace Abstract: Reward design plays a pivotal role in the training of game AIs, requiring substantial domain-specific knowledge and human effort. In recent years, s
arXiv:2605.25353v1 Announce Type: new Abstract: Inverse problems in partial differential equations (PDEs) involve estimating the physical parameters of a system from observed spatiotemporal solution f
arXiv:2605.26037v1 Announce Type: new Abstract: We test the standard RLVR tool-use recipe -- GRPO on Qwen2.5-7B-Instruct -- on a deliberately minimal knowledge-graph tool API: four Freebase navigation
arXiv:2605.24562v1 Announce Type: cross Abstract: Pedestrian intention and trajectory prediction are critical for the safe deployment of autonomous driving systems, directly influencing navigation dec
arXiv:2605.25572v1 Announce Type: cross Abstract: The growing complexity of quantum programming frameworks has exposed a critical limitation in existing large language model (LLM)-based code assistant
arXiv:2605.25010v1 Announce Type: cross Abstract: Integrating artificial intelligence (AI) into sampling-based motion planning provides new possibilities for improving autonomous navigation efficiency
arXiv:2602.19333v2 Announce Type: replace Abstract: This research introduces the first large-scale, well-balanced Persian social media text classification dataset, specifically designed to address the
arXiv:2605.25535v1 Announce Type: new Abstract: Existing large language model (LLM) based memory systems apply universal, static policies that overlook a fundamental reality: the contexts that are wor
arXiv:2605.25212v1 Announce Type: new Abstract: Federated learning (FL) is an effective paradigm for enhancing the learning capability of edge devices while preserving data privacy. In geographically
arXiv:2502.21297v2 Announce Type: replace Abstract: Persuasive dialogue is central to human communication, yet existing datasets often rely on a single language model generating both roles, producing
arXiv:2605.24621v1 Announce Type: cross Abstract: Scattering transforms achieve Lipschitz stability and translation invariance, but dense prediction tasks require preserving spatial structure lost in
arXiv:2605.25554v1 Announce Type: new Abstract: As a core task in intelligent transportation systems, traffic forecasting plays a critical role in urban traffic management. Accurate traffic forecastin
arXiv:2605.24509v1 Announce Type: cross Abstract: Latent video diffusion models generate videos by progressively transforming Gaussian noise into realistic samples conditioned on text or visual inputs
arXiv:2605.24451v1 Announce Type: new Abstract: Vietnamese exhibits substantial dialectal phonetic variation across Northern, Central, and Southern regions, where identical lexical items may be realiz
arXiv:2605.24590v1 Announce Type: cross Abstract: Low-light, long-exposure defocus deblurring remains a challenging problem due to the simultaneous presence of severe blur and complex biased noise. Ex
arXiv:2505.18190v5 Announce Type: replace-cross Abstract: Physics sensing plays a central role in many scientific and engineering domains, which inherently involves two coupled tasks: reconstructing d
arXiv:2602.07518v2 Announce Type: replace-cross Abstract: Kolmogorov-Arnold Networks (KANs) shift neural computation from linear layers to learnable nonlinear edge functions, but implementing these no
arXiv:2605.23971v1 Announce Type: cross Abstract: This work presents a physics-guided machine-learning framework for carbon monoxide concentration inference from experimentally measured resistance tra
arXiv:2601.10012v2 Announce Type: replace Abstract: Multimodal decentralized federated learning (DFL) must support collaboration among agents that hold different modality subsets and often different m
arXiv:2605.24570v1 Announce Type: cross Abstract: Despite the central role of optimization in deep learning, most optimizers rely on update structures whose functional form is fixed before training be
arXiv:2601.13236v2 Announce Type: replace-cross Abstract: Parallel imaging techniques reduce magnetic resonance imaging (MRI) scan time but image quality degrades as the acceleration factor increases.
arXiv:2601.05613v2 Announce Type: replace-cross Abstract: While collaborative forecasting on distributed time series is highly desirable, directly pooling localized datasets is often impractical due t
arXiv:2605.24421v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as analyst assistants in security operations centers (SOCs), where they ingest log and alert data t
arXiv:2605.25958v1 Announce Type: new Abstract: This paper introduces PolyGnosis 2.0, a pioneering multi-agent architecture designed to extract predictive intelligence by synthesizing Polymarket anoma
arXiv:2605.24465v1 Announce Type: new Abstract: Robots benefit from sensory information to coordinate body movement, gain robustness against perturbations, and transit between different modes to adapt
arXiv:2605.24577v1 Announce Type: cross Abstract: Independently trained transformers compute the same function in residual-stream bases that differ by a uniform random rotation on SO(d_{model}). We ca
arXiv:2605.25085v1 Announce Type: cross Abstract: We study the rate-distortion limits of online KV cache compression in autoregressive language models, formulating it as sequential Wyner-Ziv source co
arXiv:2602.01322v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) interpret neural network representations by decomposing activations into sparse combinations of dictionary atoms. H
arXiv:2605.24622v1 Announce Type: new Abstract: A robot resolving ``put the cup on that one'' must fuse gesture, language, and scene geometry, yet 3D grounding benchmarks only partially capture this r
arXiv:2605.24558v1 Announce Type: new Abstract: AI for Science (AI4Science) workflows often treat the released dataset as a fixed interface to the underlying system. However, in domains relying on ind
arXiv:2605.25271v1 Announce Type: cross Abstract: We study the symmetric polynomial prod_{alphain A_{n,d}}igl(1+alpha_1 x_1+dots+alpha_n x_nigr) where A_{n,d}:={alphainZ_{ge 0}^n:|alpha|=d}, which is
arXiv:2605.25664v1 Announce Type: cross Abstract: Poor posture is a significant concern due to its detrimental effects on health and productivity. This paper presents a collar-clipped device called Po
arXiv:2603.18363v2 Announce Type: replace-cross Abstract: Unsupervised Reinforcement Learning from Internal Feedback (RLIF) has emerged as a promising paradigm for eliciting the latent capabilities of
arXiv:2605.25704v1 Announce Type: new Abstract: In contemporary large language models (LLMs), the swish-gated linear unit (SwiGLU) activation function is widely adopted to regulate the information flo
arXiv:2605.25127v1 Announce Type: cross Abstract: Point clouds are a fundamental 3D representation in computer vision, enabling a wide range of perception tasks. However, real-world point clouds often
arXiv:2605.23934v1 Announce Type: new Abstract: Quantum computing devices are recognized as powerful tools for solving NP-complete problems. However, the intricacy of their modeling presents notable b
arXiv:2502.15835v5 Announce Type: replace-cross Abstract: Pragmatic reasoning helps interlocutors infer intended meaning from ambiguous or underspecified messages by considering shared context and cou
arXiv:2605.25894v1 Announce Type: new Abstract: Predicting stock price movements during Earnings Announcements (EAs) is a significant challenge due to market noise and high-impact price discontinuitie
arXiv:2605.13643v2 Announce Type: replace Abstract: On-policy distillation (OPD) trains a student model on its own rollouts using dense feedback from a stronger teacher. Prior literature suggests that
arXiv:2605.24775v1 Announce Type: new Abstract: Operating LLMs as coordinated multi-agent research systems over multi-hour runs surfaces failure modes that single-shot evaluation cannot: upstream prov
arXiv:2605.25362v1 Announce Type: new Abstract: The strong dynamic coupling between the manipulator and the base poses a significant challenge to maintaining spacecraft attitude stability, potentially
arXiv:2605.26110v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) achieve versatility by reformulating diverse tasks into a unified instruction-following framework via instruc