Knowledge catalogue
arXiv:2608.07405v1 Announce Type: cross Abstract: Foundation segmentation models can provide supervision for spacecraft imagery without manual training masks, but their predictions vary with textual p
arXiv:2608.07283v1 Announce Type: new Abstract: Grammar engineering requires expertise in linguistic formalism and computational implementation, especially in parallel grammar projects that balance cr
arXiv:2604.06756v2 Announce Type: replace Abstract: Large language models (LLMs) has been widely adopted as a scalable surrogate for human evaluation, yet such judges remain imperfect and susceptible
arXiv:2608.07285v1 Announce Type: cross Abstract: AI-generated music is increasingly used at the stem level, with producers integrating synthetic drums, basslines, or vocals alongside human-performed
arXiv:2608.07118v1 Announce Type: new Abstract: Credit assignment in multi-turn agent reinforcement learning operates at two levels: assigning trajectory-level credit to actions and distributing each
arXiv:2608.06898v1 Announce Type: cross Abstract: Researchers who seek to build social robot applications on foundation models are faced with a difficult question: how should we pick a model? Public l
arXiv:2608.07018v1 Announce Type: cross Abstract: Horizon detection in images of ice-covered waters is a challenging problem for maritime navigation due to low contrast between water and sky, cluttere
arXiv:2603.27435v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly being used to generate comprehensive, knowledge-intensive reports. However, while these models a
arXiv:2603.21607v2 Announce Type: replace Abstract: While retrieval-augmented generation (RAG) significantly improves the factual reliability of LLMs, it does not eliminate hallucinations, so robust u
arXiv:2608.06803v1 Announce Type: cross Abstract: Ising machines are emerging as promising hardware for combinatorial optimization. With recent advances in CMOS Ising technology, they are becoming att
arXiv:2608.07074v1 Announce Type: new Abstract: Dense point cloud maps, as a typically used mapping representation, are difficult to deploy on resource-constrained robots because their memory consumpt
arXiv:2608.07208v1 Announce Type: cross Abstract: Existing measures of how much a text is about a concept read the surface of the text: dictionary word shares, topic proportions, embedding similaritie
arXiv:2608.07180v1 Announce Type: cross Abstract: Recent advances in deep reinforcement learning (RL) have shown that improving neural network architectures can yield substantial gains in sample effic
arXiv:2608.06378v1 Announce Type: cross Abstract: Driver emotions can affect risk perception, decision-making, and vehicle control under complex road conditions. Existing studies mainly focus on drive
Hey LocalLlaMa, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots a
arXiv:2608.07040v1 Announce Type: new Abstract: Solving combinatorial optimization problems (COPs) requires not only efficient algorithms but also carefully crafted formulations. While recent works ha
arXiv:2509.16664v2 Announce Type: cross Abstract: Retrieval systems rely on representations learned by increasingly powerful models. However, due to the high training cost and inconsistencies in learn
arXiv:2608.06701v1 Announce Type: cross Abstract: Fixing GitHub issues in large-scale projects is a long-horizon task, especially when a fix requires changes across multiple locations or the issue des
arXiv:2608.07444v1 Announce Type: cross Abstract: Accurate user equipment (UE) localization is critical for beam management in reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave
arXiv:2608.06802v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts with token-level supervision from teacher models, but its effectiveness can depend str
arXiv:2509.00559v3 Announce Type: replace Abstract: Humans intuitively navigate social interactions by simulating unspoken dynamics and reasoning about others' perspectives, even with limited informat
arXiv:2608.06907v1 Announce Type: new Abstract: Legged robots require robust agility to perceive and interact with complex and dynamic environments within a constrained time. However, most existing qu
arXiv:2510.09904v2 Announce Type: replace-cross Abstract: Despite their widespread use, training deep Transformers can be unstable. Layer normalization, a standard component, improves training stabili
arXiv:2608.06477v1 Announce Type: cross Abstract: Computer-use agents (CUAs) face a growing threat from indirect prompt injection, where adversarial instructions are planted in the environment such as
arXiv:2509.05208v2 Announce Type: replace Abstract: Large language models (LLMs) excel at program synthesis, yet their ability to produce symbolic graphics programs (SGPs) that render into precise vis
arXiv:2608.06587v1 Announce Type: cross Abstract: Robot swarms utilize many independent limited-sensing agents to produce complex emergent behaviors without requiring centralized control. However, lit
arXiv:2608.07106v1 Announce Type: new Abstract: Deploying three-dimensional deep learning frameworks to low-power embedded processors is bottlenecked by the unstructured nature of spatial data and the
arXiv:2608.07446v1 Announce Type: cross Abstract: Rapid adoption of large language models (LLMs) in enterprise settings has introduced operational, security, and governance risks. As generative AI app
The next frontier of Recursive Self-Improvement is Physical AI. Japan sparked the robotics revolution. We are expanding our RSI Lab to build world models that allow agentic reasoning systems to recurs
MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here. Way back in the summer of 2017,
arXiv:2608.06657v1 Announce Type: new Abstract: Modern cyber-physical and AI-assisted systems couple human operators, AI decision modules, and automated controllers in a single control loop, so trustw
arXiv:2608.07077v1 Announce Type: new Abstract: The Tower of Hanoi is a simple planning puzzle that in prior work has proven challenging for large reasoning models (LRMs). Current models solve the sta
arXiv:2608.06934v1 Announce Type: cross Abstract: Visual perception of walkability varies substantially across individuals, reflecting differences in personal characteristics, experiences, and prefere
arXiv:2608.06673v1 Announce Type: new Abstract: Language descriptions in source-free cross-domain few-shot learning (SF-CDFSL) are often selected according to zero-shot accuracy obtained with a frozen
table bench https://huggingface.co/bartowski/endless-frontier_BigBang-v1-GGUF I'm downloading this model only because Bartowski converted it to .gguf, so it might be interesting. Doubts : The headline
arXiv:2608.06354v1 Announce Type: new Abstract: We present a MR safe, master-slave robot manipulator for abdominal interventions in the MRI chamber. A human operated 2+1-DoF master controller manipula
arXiv:2608.05221v1 Announce Type: new Abstract: The ongoing digitalization of rail systems and the increasing use of artificial intelligence (AI) are fundamentally transforming the design, operation,
arXiv:2608.05791v1 Announce Type: cross Abstract: Large language model (LLM)-driven multi-agent systems typically require multiple model invocations and complex coordination during inference, and thei
arXiv:2608.05840v1 Announce Type: new Abstract: Accurate vehicle localization from monocular roadside surveillance cameras is important for intelligent transportation systems, traffic monitoring, and
arXiv:2509.16684v2 Announce Type: replace Abstract: Multi-view crowd counting and localization fuse the input multi-views for estimating the crowd number or locations on the ground. Existing methods m
arXiv:2509.10482v2 Announce Type: replace-cross Abstract: The increasing sophistication of technology systems makes traditional threat modeling hard to scale, especially for small organizations with l
arXiv:2503.03556v3 Announce Type: replace Abstract: Object affordance reasoning, the ability to infer object functionalities based on physical properties, is fundamental for task-oriented planning and
arXiv:2608.05255v1 Announce Type: cross Abstract: Retail investors lack access to the kind of personalized, tax-aware portfolio management that institutional clients take for granted -- existing robo-
arXiv:2006.04156v2 Announce Type: replace Abstract: Our inferences in the real world are rarely naive - we acquire experiences through our lifetime that can help us more quickly understand the structu
arXiv:2606.18519v2 Announce Type: replace-cross Abstract: Though robotic systems are now being commercialized and deployed in various industries, many of these systems are highly specialized and often
arXiv:2608.05723v1 Announce Type: new Abstract: Providing assistance across diverse movements is a central objective of exoskeletons, and anatomical knowledge can enable responsive support that genera
arXiv:2608.05250v1 Announce Type: new Abstract: Multi-task supervised fine-tuning (SFT) often casts a heterogeneous data mixture as a single optimization problem, even though different tasks may reach
arXiv:2608.05155v1 Announce Type: cross Abstract: Traditional sentiment analysis (SA) models, while effective for polarity classification, provide limited insight into the rhetorical, ideological, and
arXiv:2606.16891v2 Announce Type: replace-cross Abstract: Federated Learning is rapidly evolving beyond the exchange of traditional model weights and gradients, yet existing definitions fail to captur
arXiv:2608.06023v1 Announce Type: new Abstract: To address the limitations of video-based emotion recognition under ambiguous or socially masked behavioral cues, as well as the poor deployability of p
arXiv:2608.06352v1 Announce Type: cross Abstract: Training terminal agents requires executable and verifiable tasks that are not merely solvable, but appropriately challenging for learning. Executable
arXiv:2608.05176v1 Announce Type: cross Abstract: Music education has never been a static discipline. Each major technological shift has forced educators and institutions to reconsider what they teach
arXiv:2508.02091v4 Announce Type: replace-cross Abstract: Approximate nearest-neighbor search (ANNS) algorithms have become increasingly critical for recent AI applications, particularly in retrieval-
arXiv:2608.00641v2 Announce Type: replace Abstract: Bayesian optimization (BO) relies on a surrogate model and an acquisition function, yet the most suitable choices vary across tasks and optimization
arXiv:2511.04949v2 Announce Type: replace-cross Abstract: Rapid advances in generative AI have led to increasingly realistic deepfakes, posing growing challenges for law enforcement and public trust.
arXiv:2608.05811v1 Announce Type: new Abstract: Pixel-space generative models bypass lossy latent compression, yet necessitate joint learning of global structure and fine-grained details in a high-dim
arXiv:2608.05605v1 Announce Type: cross Abstract: Research and Education Networks (RENs) serve as critical infrastructure for scientific discovery, yet they face a unique security paradox: their norma
arXiv:2602.11834v2 Announce Type: replace-cross Abstract: While machine learning (ML)-based receiver algorithms have received a great deal of attention in the recent literature, they often suffer from
arXiv:2608.06208v1 Announce Type: new Abstract: Contact-centric tasks on surfaces, ranging from inspection and cleaning to sanding and polishing, require robots to systematically cover the surface whi
arXiv:2608.05265v1 Announce Type: cross Abstract: Prediction of post-wildfire debris flows is critical for mitigating hazards to communities, infrastructure, and resources during intense rainfall in r