Knowledge catalogue
arXiv:2609.04271v1 Announce Type: new Abstract: Wi-Fi-based human activity recognition (HAR) has become an important part of integrated sensing and communications, paving the way for a range of contex
arXiv:2609.04714v1 Announce Type: cross Abstract: Striking a balance between helpfulness and safety remains a fundamental challenge in aligning large language models. To achieve this balance, models s
arXiv:2609.04763v1 Announce Type: new Abstract: Due to resource constraints or external and internal uncertainties, clients in real-world federated learning systems are often intermittently available
arXiv:2609.04273v1 Announce Type: cross Abstract: Scalable video coding (SVC) encodes a video into a layered bitstream consisting of a base layer and one or multiple enhancement layers, enabling decod
arXiv:2609.04634v1 Announce Type: cross Abstract: As generative audio models grow in complexity, the computational and ecological costs of synthesizing everyday sounds have become increasingly prohibi
arXiv:2609.05262v1 Announce Type: new Abstract: Computational phylogenetics has become an essential tool in historical linguistics, yet its application at a global scale remains constrained by two fac
arXiv:2601.18049v2 Announce Type: replace Abstract: Significant progress has been made in semi-supervised hyperspectral image (HSI) classification regarding feature extraction and classification perfo
arXiv:2609.05174v1 Announce Type: new Abstract: Explainability is increasingly seen as a crucial requirement in AI-based medical diagnosis, particularly in safety-critical clinical decision-making. Mo
arXiv:2609.04931v1 Announce Type: new Abstract: The widespread adoption of artificial intelligence (AI) within real-world applications has raised a lot of concerns regarding their trustworthiness, esp
arXiv:2609.04984v1 Announce Type: new Abstract: In the field of computer vision and graphics, high-quality reconstruction of the human body in static scenes has been achieved in recent years by a sing
arXiv:2603.21309v4 Announce Type: replace Abstract: Facial expression recognition (FER) in videos requires model personalization to capture considerable variation across subjects. Vision-language mode
arXiv:2410.23440v4 Announce Type: replace Abstract: Operator learning, the approximation of mappings between infinite-dimensional function spaces using machine learning, has gained increasing research
arXiv:2609.05388v1 Announce Type: new Abstract: Visual reasoning tasks require a system to jointly perceive visual content and apply formal relational constraints---a combination that neither pure neu
arXiv:2609.05084v1 Announce Type: new Abstract: Reliable autonomous mapping, environmental sampling, last-mile logistics, and infrastructure deployment depend on the optimal surface area-balanced dist
arXiv:2508.06207v3 Announce Type: replace Abstract: Back-support exoskeletons mitigate musculoskeletal strain, yet current systems rely on reactive sensing and lack context-aware assistance modulation
arXiv:2503.08904v3 Announce Type: replace Abstract: The recent developments in data-driven methods have paved the way to new methodologies to provide accurate state reconstruction of engineering syste
arXiv:2609.04637v1 Announce Type: cross Abstract: Audio Large Language Models (Audio LLMs) have advanced in audio understanding, yet they can still predict the answer by reasoning from textual cues or
arXiv:2609.04417v1 Announce Type: cross Abstract: Distributed AI training involves recurring rounds of data exchange between multiple pairs of GPU nodes. Slowdown in even one flow due to congestion ca
arXiv:2609.05198v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has emerged as a widely adopted post-training paradigm for enhancing large language models in reasoning domains. However, t
arXiv:2609.04806v1 Announce Type: new Abstract: Financial large language models are increasingly deployed for summarization of reports and disclosures, where numerical hallucination poses significant
arXiv:2609.04962v1 Announce Type: new Abstract: What is the relation between understanding and compression, and why does human understanding take such a heavily compressed form? Across information the
I read some strange criticisms of this post. So here is my take. I’m not fully endorsing the piece by Newport, but there’s quite some factually true information in it. Responsible and careful people (
GPT-6 is pretty good tbh @viktaur27 @Teslarati The rate of improvement from original GPT to GPT-3 is impressive. If this rate of improvement continues, GPT-5 or 6 could be indistinguishable from the s
Hiya, NInfer is amazng for Qwen, but lacking for real-world-use. As adoption of issues/pr's was not really what I needed, I created a fork and hit it for this week with 3 concurrent claude code sessio
I was running into a lot of posts that praised both the Fixed template and the Sharp template in comparison to the stock one, so I put them to the test. It's not as extensive as it should be for a pap
This is a weird behavior in coding models and something worth looking into. It turns that some models over-edit code that another models wrote. There is a high chance that your repo now has commits fr
arXiv:2609.03891v1 Announce Type: new Abstract: Semantic mapping plays a crucial role in the ability of a robot to interact with objects, operate and navigate a complex environment. The most common pi
arXiv:2609.03337v1 Announce Type: new Abstract: Every engineered fill is specified by a maximum dry density and an optimum moisture content. Each determination needs a full Proctor test. Published cor
arXiv:2609.03505v1 Announce Type: new Abstract: Anomaly detection in Internet of Things (IoT) networks presents unique challenges due to the diversity of devices, lack of labeled data, and domain vari
arXiv:2206.05215v2 Announce Type: replace Abstract: K-Means clustering algorithm is one of the most commonly used clustering algorithms because of its simplicity and efficiency. K-Means clustering alg
arXiv:2603.16718v2 Announce Type: replace Abstract: LLMs perform strongly across NLP, but their ability to produce explicit grammatical analyses remains unclear. Arabic provides a challenging testbed
arXiv:2609.03716v1 Announce Type: new Abstract: Data centers are increasingly optimized by artificial intelligence and, at the same time, increasingly loaded by it. The literature treats these as two
arXiv:2609.03362v1 Announce Type: new Abstract: Grasping and holding tools while using them presents a considerable challenge not only for robots but also for humans. Such a challenge is particularly
arXiv:2609.03970v1 Announce Type: new Abstract: Accurate identification of weld seam geometries is essential for automated robotic post processing operations such as grinding, finishing, and inspectio
arXiv:2609.03151v1 Announce Type: cross Abstract: Long-context reasoning for large language models (LLMs) is becoming increasingly important, but training over long sequences remains challenging due t
arXiv:2609.03734v1 Announce Type: cross Abstract: BLEU-4 is the standard metric for evaluating sign language translation (SLT), but spoken-language metrics may not adequately reflect sign language pro
arXiv:2609.02895v1 Announce Type: new Abstract: Large-scale public events, such as religious festivals, political rallies, and cultural gatherings, are increasingly vulnerable to the rapid disseminati
arXiv:2609.03901v1 Announce Type: cross Abstract: We present a comparative evaluation of six information retrieval methods for the task of academic advisor discovery: ranking CS faculty members by rel
arXiv:2609.03977v1 Announce Type: cross Abstract: Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent
arXiv:2609.02892v1 Announce Type: cross Abstract: Single-turn code-generation metrics understate a central property of deployed agents: whether they can repair a wrong artifact after receiving concret
arXiv:2408.05301v3 Announce Type: replace Abstract: Humans often work closely together and relay a wealth of information through physical interaction. Robots, on the other hand, are not yet able to wo
arXiv:2609.03064v1 Announce Type: cross Abstract: Federated learning allows banks, hospitals, and other regulated organizations to train a shared model without moving raw records off their own servers
arXiv:2503.04580v3 Announce Type: replace Abstract: Robust and accurate proprioceptive state estimation of the main body is crucial for legged robots to execute tasks in extreme environments where ext
arXiv:2609.03680v1 Announce Type: new Abstract: Labelling vision datasets, especially for segmentation tasks, is a laborious and costly process that stymies novel developments in agricultural robotics
arXiv:2609.04031v1 Announce Type: new Abstract: Video diffusion models (VDMs) have achieved impressive progress in text-to-video generation, but their high memory and computational costs hinder practi
arXiv:2609.02901v1 Announce Type: new Abstract: Modern automatic speech recognition (ASR) scenarios require both spoken-form transcripts for faithful transcription and readable written-form transcript
arXiv:2609.04128v1 Announce Type: new Abstract: Scaling interactive and verifiable environments is critical for training terminal agents. As frontier models become more capable, environments synthesiz
arXiv:2609.03662v1 Announce Type: new Abstract: Recent unlearning methods (e.g. NPO, DPO, LUNAR) make use of refusal alignment to suppress forgotten data. However, it has been shown that refusal respo
arXiv:2609.03222v1 Announce Type: new Abstract: Certifiable methods have arisen as a means to guarantee global optimality of solutions to non-convex problems using convex semidefinite programming (SDP
arXiv:2609.03384v1 Announce Type: new Abstract: In-Context Segmentation (ICS) aims to precisely segment arbitrary semantic concepts, such as objects or parts, given one or a few annotated visual exemp
arXiv:2609.03590v1 Announce Type: cross Abstract: Timely delivery of delay-sensitive information over dynamic, heterogeneous networks is essential for NextG interactive applications, yet providing str
arXiv:2609.03724v1 Announce Type: cross Abstract: Bayesian Network (BN) fusion combines multiple input networks into a single structure, balancing dependency preservation with computational tractabili
arXiv:2609.03067v1 Announce Type: new Abstract: World models are an emerging paradigm in representation learning in which an agent jointly learns state-action dynamics and observation models from offl
arXiv:2405.21047v4 Announce Type: replace Abstract: Large Language Models (LLMs) struggle with reliably generating highly structured outputs, such as program code, mathematical formulas, or well-forme
arXiv:2609.03442v1 Announce Type: new Abstract: Differentiable causal discovery methods increasingly encode expert priors as forbidden-edge constraints enforced by an Augmented Lagrangian (ALM) penalt
arXiv:2609.03781v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in multilingual settings, yet their safety is still evaluated primarily in English. This limits our
arXiv:2609.03883v1 Announce Type: new Abstract: Creatures that display 'hedonic place preference behaviour' are thought by many scientists to experience feelings, on the assumption that their attracti
arXiv:2607.14415v2 Announce Type: replace Abstract: Computed Tomography (CT) carries significant ionizing radiation risks, driving the need for sparse-view reconstruction. Implicit scene representatio
arXiv:2503.16551v4 Announce Type: replace Abstract: Control barrier functions (CBFs) provide a principled framework for safety-critical control, but their construction typically requires an explicit a
arXiv:2609.03630v1 Announce Type: new Abstract: Autonomous unmanned aerial vehicles (UAVs) increasingly operate in cluttered environments where global planners such as RRT* are not directly deployable