Knowledge catalogue
arXiv:2606.25542v1 Announce Type: new Abstract: Micro-expression recognition (MER) is challenging due to subtle facial movements, limited data, and the ambiguous relationship between Action Units (AUs
arXiv:2501.15373v2 Announce Type: replace-cross Abstract: Merely pursuing performance may adversely affect safety, while a conservative policy for safe exploration will degrade the performance. How to
arXiv:2606.25497v1 Announce Type: new Abstract: Object-Goal Navigation (ObjNav) requires embodied agents to autonomously locate specified targets using only egocentric visual observations. Existing mo
arXiv:2606.26079v1 Announce Type: new Abstract: Standard benchmarks for multimodal large language models (MLLMs) score each item on one canonical ordering and miss whether order-irrelevant shuffling c
arXiv:2606.24987v1 Announce Type: cross Abstract: Optimal transport (OT) has become a central language for comparing probability measures, but exact balanced OT is often both too rigid for data with m
arXiv:2510.07094v2 Announce Type: replace Abstract: This work focuses on sampling strategies of configuration variations for generating robust universal locomotion policies for quadrupedal robots. We
arXiv:2606.25821v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) architectures have emerged as an increasingly influential paradigm as they offer a strategic balance between parameter s
arXiv:2606.25369v1 Announce Type: cross Abstract: While large language model (LLM)-based text-to-speech (TTS) systems have achieved high-quality speech synthesis, most existing systems focus on Englis
arXiv:2606.25006v1 Announce Type: new Abstract: Target-specific peptide design requires sequence and structure co-design under full atom geometric constraints. Latent generative frameworks offer an ef
arXiv:2509.22193v2 Announce Type: replace Abstract: Distilling reasoning traces from strong teacher models has become the standard recipe for building capable small language models. Yet reasoning trac
arXiv:2606.25619v1 Announce Type: new Abstract: Accurate metric-space hand pose estimation (HPE) is essential for immersive human-computer interaction and robotics. However, most existing methods pred
arXiv:2509.26376v3 Announce Type: replace Abstract: Test-time strategies have shown remarkable success in improving large language models, but their application to next-token prediction (NTP) autoregr
arXiv:2606.18936v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly embedded in AI for Science (AI4Science) workflows, from scientific question answering and literature a
arXiv:2603.20452v2 Announce Type: replace Abstract: Longitudinal neuroimaging is essential for modeling disease progression in Alzheimer's disease (AD), yet irregular sampling and missing visits pose
arXiv:2606.25959v1 Announce Type: cross Abstract: Conventional audio pipelines typically treat speech enhancement (SE) and automatic gain control (AGC) as discrete modules, which often limits overall
arXiv:2601.23147v2 Announce Type: replace Abstract: The integrity of time in distributed Internet of Things (IoT) devices is crucial for reliable operation in energy cyber-physical systems, such as sm
arXiv:2606.25533v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for enhancing large language models with external knowledge. By coupling retri
arXiv:2606.25348v1 Announce Type: new Abstract: Tactile sensing is essential for humanoid robots to achieve safe physical interaction, dexterous manipulation, and truly human-like responsiveness. Howe
arXiv:2606.24933v1 Announce Type: cross Abstract: Recent advances in quantum machine learning have motivated efficient models for sequential data processing. In this paper, we propose Self-Modulating
arXiv:2606.25232v1 Announce Type: cross Abstract: Ordered bottlenecks aim to provide utility at flexible budgets by assigning coarse information to early tokens and task-relevant detail to later ones.
arXiv:2606.25852v1 Announce Type: new Abstract: Group-based reinforcement learning effectively post-trains LLM agents for long-horizon, sparse-reward tasks by deriving step-level credit from trajector
arXiv:2606.24935v1 Announce Type: new Abstract: Thin-structure segmentation--power lines, cracks, lane markings at 1-3 pixel width--requires preserving connectivity that standard representations precl
arXiv:2606.25552v1 Announce Type: new Abstract: Prompt-based spoken language understanding (SLU) with large language models (LLMs) often suffers from inconsistent intent--slot structures due to decodi
arXiv:2508.07952v2 Announce Type: replace Abstract: Clustering algorithms often assume all features contribute equally to the data structure, an assumption that usually fails in high-dimensional or no
arXiv:2606.25818v1 Announce Type: new Abstract: Shift-variant image degradation is frequently encountered in practical imaging systems where the point spread function (PSF) varies across the image fie
arXiv:2606.25763v1 Announce Type: new Abstract: Real-world photography requires capture-time guidance for both camera framing and subject pose. Yet existing aesthetic cropping benchmarks mainly evalua
arXiv:2606.25151v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) embed governing equations in their loss function, enabling mesh-free solutions to partial differential equation
arXiv:2602.17104v2 Announce Type: replace-cross Abstract: We propose a streamlined spectral algorithm for community detection in the two-community stochastic block model (SBM) under constant edge dens
arXiv:2606.18837v2 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based automatic Multi-Agent Systems (MAS) generation has become a crucial frontier for tackling complex tasks. Howe
arXiv:2606.24890v1 Announce Type: new Abstract: Can a small group of volunteers shape how AI systems discuss animal welfare, just by editing Wikipedia? We show that they can. Wikipedia appears in near
arXiv:2606.17945v2 Announce Type: replace Abstract: Large language models provide a tractable system for asking how intelligence itself emerges, rather than only how LLMs can be engineered. Although p
arXiv:2606.25195v1 Announce Type: cross Abstract: The increasing use of AI systems for code generation raises a central security question: what can today's models and coding agents actually do to prod
arXiv:2606.24991v1 Announce Type: cross Abstract: Model Predictive Control (MPC) is widely used in industrial and robotic systems for enforcing constraints and embedding domain knowledge through finit
arXiv:2606.25777v1 Announce Type: cross Abstract: We initiate a resource-aware theory of extit{language generation in the limit} under the minimal constraint of space efficiency. In our framework, a l
arXiv:2606.25495v1 Announce Type: new Abstract: Saudi Telecom Company (STC) is among the most popular companies in Saudi Arabia, with many customers. Yet, there is still a big room for improvement in
arXiv:2602.06566v3 Announce Type: replace-cross Abstract: Despite recent successes, test-time scaling -- i.e., dynamically expanding the token budget during inference as needed -- remains brittle for
arXiv:2312.00206v4 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has recently enabled real-time rendering of unbounded 3D scenes for novel view synthesis. However, this technique requi
arXiv:2606.25535v1 Announce Type: new Abstract: Quantitative maps from dynamic contrast-enhanced MRI (DCE-MRI) are essential for tumor assessment but are often unavailable due to contrast-agent risks
arXiv:2606.25224v1 Announce Type: new Abstract: Learning-based automated coaching systems for complex motor tasks such as high-performance driving remain limited in the ability to be adaptive by their
arXiv:2606.20615v2 Announce Type: replace Abstract: AI agents now participate as first-class team members across the software development lifecycle, yet no specification language exists for expressing
arXiv:2606.25097v1 Announce Type: new Abstract: Speculative decoding accelerates inference by letting a draft model propose tokens for a target model to verify, raising a concrete safety question: at
arXiv:2603.10371v2 Announce Type: replace-cross Abstract: Speech tokenizers are essential for connecting speech to large language models (LLMs) in multimodal systems. Speech tokenizers are expected to
arXiv:2606.25990v1 Announce Type: new Abstract: As multimodal conversational systems increasingly engage in spoken interaction, their ability to navigate paralinguistic social cues has become a critic
arXiv:2512.05354v2 Announce Type: replace Abstract: The rise of 3D Gaussian Splatting has revolutionized photorealistic 3D asset creation, yet a critical gap remains for their interactive refinement a
arXiv:2601.21416v2 Announce Type: replace Abstract: The generalization capabilities of robotic manipulation policies are heavily influenced by the choice of visual representations. Existing approaches
arXiv:2606.25634v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable progress in single-image perception, yet their ability to reason about complex cross-view
arXiv:2606.25269v1 Announce Type: cross Abstract: As black-box models become foundational to modern research, ensuring their stability is paramount for the realization of trustworthy artificial intell
arXiv:2606.24940v1 Announce Type: cross Abstract: Predicting transcriptional responses to genetic perturbations could reduce the experimental burden of functional genomics, but extrapolation to genes
arXiv:2606.25754v1 Announce Type: new Abstract: Polishing is a critical finishing process in high-end manufacturing fields such as aerospace, where surface quality directly affects the service perform
arXiv:2606.25335v1 Announce Type: new Abstract: Multi-Agent Reinforcement Learning (MARL) value factorization methods can suffer from a loss of plasticity, gradually failing to adapt when transferring
arXiv:2606.25765v1 Announce Type: new Abstract: Climbing hollow stairs remains a challenging problem for quadruped robots due to the high risk of leg trapping, severe depth sparsity, and high-frequenc
arXiv:2606.25329v1 Announce Type: new Abstract: State Space Models (SSMs), designed for long-range modeling, offer linear computational complexity and strong capabilities in capturing long-range depen
arXiv:2606.25601v1 Announce Type: cross Abstract: Hyperparameter selection is a critical step in the deployment of modern artificial intelligence systems, given the need to tune degrees of freedom suc
arXiv:2606.25632v1 Announce Type: new Abstract: Recent LLM role-playing systems build character agents from novels by extracting characters, scenes, and relations. Yet long-narrative role-playing suff
arXiv:2606.25529v1 Announce Type: cross Abstract: Speech-to-speech translation (S2ST) should preserve not only lexical meaning, but also expressive attributes: emotion, scenario style (e.g., news repo
arXiv:2606.25657v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) have shown promise for analyzing language models, but applying them to vision-language models (VLMs) often yields representat
arXiv:2606.25379v1 Announce Type: new Abstract: I treat a book as a point in a sentence-embedding space and a literary transformation as an operation on points. Given an original novel and its sequel,
arXiv:2601.17917v3 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) offer a compelling paradigm for natural language generation, leveraging parallel decoding and bidirect
arXiv:2310.09149v3 Announce Type: replace-cross Abstract: We study the approximation of probability measures in the Wasserstein-p distance by structured classes of approximators, motivated by applicat
arXiv:2606.25234v1 Announce Type: new Abstract: What is the geometry of a visual percept? The most widely used protocols for decomposing neural network representations into interpretable parts treat c