Knowledge catalogue
arXiv:2609.18540v1 Announce Type: new Abstract: Most keyframe selection studies focus on offline settings, assuming access to the full video and query in advance. In contrast, real-world streaming sce
arXiv:2609.18497v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong performance across diverse robotic manipulation tasks, yet their predominantly vision-centr
arXiv:2609.17992v1 Announce Type: cross Abstract: A UAV mobile edge computing (MEC) fleet trades energy against delay, and its schedules form a Pareto front; we call a scheduler operable when the flee
The other problem with the pretense that liability law might solve our problems is that our existing federal government has shown little interest in prosecuting or even investigating potential violati
arXiv:2609.18676v1 Announce Type: new Abstract: Generative artificial intelligence (GenAI) is changing how students learn, yet the roles of course context, cognitive reliance, evaluation literacy, and
arXiv:2512.24100v2 Announce Type: replace Abstract: Current state-of-the-art paradigms predominantly treat Text-to-Motion (T2M) generation as a direct translation problem, mapping symbolic language di
This might be the biggest admission in any of the 100+ AI copyright lawsuits. OpenAI & Microsoft execs admit the case is about “the largest theft of labor in human history”, that publishers face an “e
arXiv:2609.18112v1 Announce Type: cross Abstract: LLM serving is typically offered as a shared, multi-tenant service, where high-demand workloads from one client can cause latency SLO violations for o
arXiv:2603.14005v2 Announce Type: replace Abstract: To generalize deepfake detectors to future unseen forgeries, most existing methods attempt to simulate the dynamically evolving forgery types using
arXiv:2609.18853v1 Announce Type: cross Abstract: A central challenge across control and learning is the design of mechanisms regulating the interactions between humans and autonomous agents. Inspired
arXiv:2609.18697v1 Announce Type: new Abstract: Historians have reconstructed the twentieth-century transformation of general relativity and gravitation (GRG) at the field level and through individual
arXiv:2609.18321v1 Announce Type: cross Abstract: Offline on-policy distillation gains efficiency by collecting student trajectories and teacher supervision once and reusing them throughout optimizati
arXiv:2609.18585v1 Announce Type: cross Abstract: Text-to-music (TTM) systems are increasingly used to generate musical audio from natural-language descriptions. Robust evaluation is therefore essenti
arXiv:2609.18232v1 Announce Type: new Abstract: Real-robot demonstrations are limited, motivating the use of human manipulation data collected without robots, including egocentric videos and handheld
arXiv:2409.09253v2 Announce Type: replace-cross Abstract: Owing to the unprecedented capability in semantic understanding and logical reasoning, large language models (LLMs) have shown fantastic poten
arXiv:2604.04502v2 Announce Type: replace Abstract: Video generation models can produce coherent vi- sual sequences depicting object motion and interactions. We in- vestigate how frontier video genera
arXiv:2609.17714v1 Announce Type: new Abstract: Real-world robotic disassembly requires long-horizon execution, where robots must perform ordered sequences of manipulation tasks across multiple parts
arXiv:2508.06291v2 Announce Type: replace Abstract: Semantic scene understanding in robotics requires representations that are both metric-accurate and queryable via natural language in real-time. Whi
arXiv:2609.18451v1 Announce Type: new Abstract: We present a hierarchical UAV navigation framework that aligns natural-language intent with dynamically feasible flight behaviors in cluttered indoor en
On July 28, user NIK (@ns123abc) posted a brief tweet claiming that former OpenAI CEO Sam Altman had directed an AI to hack into Hugging Face. According to the narrative, the AI carried out the break‑
arXiv:2609.17772v1 Announce Type: cross Abstract: AI-generated covariates from notes, conversations, images, and wearable streams can change the causal question when their roles are left unspecified.
arXiv:2609.17977v1 Announce Type: new Abstract: Emotion recognition in conversation (ERC) is a production capability behind agent-assist prompts, escalation routing, and post-call analytics in contact
arXiv:2609.17571v1 Announce Type: cross Abstract: Where in a Transformer is the change from memorization to generalization functionally expressed? We introduce Transition Games--behavior-aligned exact
arXiv:2609.18272v1 Announce Type: new Abstract: Agentic AI systems plan, invoke tools and act with limited supervision; they are now both the subject of audits and, increasingly, the auditor. Independ
arXiv:2609.17989v1 Announce Type: cross Abstract: Large language models (LLMs) now serve as conversational shopping assistants on platforms that also sell advertising. These AI agents face a conflict
arXiv:2609.16541v1 Announce Type: cross Abstract: We test the performance of agents for automated network intrusion response in a cyber range intended for human operator training. The range implements
arXiv:2609.16854v1 Announce Type: new Abstract: Probability is fundamental to theories of language comprehension, production, acquisition, and evolution, as well as to large language models. Existing
arXiv:2609.16413v1 Announce Type: cross Abstract: Laboratory automation can improve experimental throughput, accessibility, and reproducibility, but many robotic laboratory systems remain difficult to
arXiv:2609.16192v1 Announce Type: cross Abstract: The current trend of digitalisation has revolutionised the organisation of work and the way it is measured and performed across the globe, with AI bec
arXiv:2601.11716v2 Announce Type: replace-cross Abstract: Accurate and efficient detector simulation is essential for modern collider experiments. To reduce the high computational cost, various fast m
article in no way whatsoever supports the headline. trash. Meet Anthropic CEO Dario Amodei’s handpicked super-woke globalists he thinks will save us from an AI apocalypse. Read today's cover here: htt
arXiv:2609.16213v1 Announce Type: new Abstract: Artificial intelligence is reshaping biological research across an increasingly connected digital-to-physical workflow. General-purpose large language m
arXiv:2609.16369v1 Announce Type: new Abstract: Precise manipulation of liquid droplets underpins lab-on-a-chip platforms for diagnostics, chemical synthesis, and biological assays. Yet autonomous dro
arXiv:2609.16501v1 Announce Type: cross Abstract: De-identified resume screening assumes that redacting explicit fields prevents ethnocultural inference; however, recent audits attribute residual leak
arXiv:2609.16937v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as an effective approach for large language model post-training, yet existing objectives face a trade-off bet
arXiv:2609.15995v1 Announce Type: new Abstract: Emerging AI regulation mandates bias audits of high-risk systems, and audit scores are beginning to be used to rank models. Both uses assume different a
arXiv:2609.17477v1 Announce Type: cross Abstract: The absolute capacity of dense associative memory has mainly been analyzed for unbiased patterns. Here we examine the effect of bias in centered binar
arXiv:2603.00156v2 Announce Type: replace Abstract: Medical image segmentation is a cornerstone of computer-assisted diagnosis and treatment planning. While recent multimodal vision-language models ha
arXiv:2609.17265v1 Announce Type: cross Abstract: Training multi-agent drone-swarm policies directly in high-fidelity (HF) rigid-body physics is accurate but computationally expensive. This cost scale
arXiv:2609.16206v1 Announce Type: new Abstract: Disaggregated LLM serving places compute heavy prefill and memory heavy decode on separate GPU pools. Systems such as DistServe, Splitwise, and Mooncake
arXiv:2603.15547v2 Announce Type: replace-cross Abstract: Modeling student misconceptions in a realistic manner is critical for AI in education. In this work, we examine how large language models (LLM
arXiv:2512.22478v2 Announce Type: replace Abstract: Numerous studies on Boosting attempt to mitigate classification bias caused by class imbalance. However, existing studies have yet to explore the co
arXiv:2609.15996v1 Announce Type: new Abstract: Chen, Zhao, and Cohan introduce a valuable distributional evaluation of LLM-generated research ideas. This comment raises a narrower identification conc
arXiv:2609.17474v1 Announce Type: cross Abstract: Large language model (LLM) distillation aims to transfer the capabilities of a powerful teacher to a smaller student. Direct imitation, however, can a
arXiv:2609.16149v1 Announce Type: new Abstract: Despite steady progress in face recognition, current face recognition models still suffer from significant demographic biases. While approaches for bias
arXiv:2512.23650v3 Announce Type: replace Abstract: Humans intuitively move to sound, but current humanoid robots lack expressive improvisational capabilities, confined to predefined motions or sparse
arXiv:2509.12626v4 Announce Type: replace-cross Abstract: Aligning agentic AI with user intent is critical for delegating complex, socially embedded tasks, yet user preferences are often implicit, evo
arXiv:2609.16689v1 Announce Type: new Abstract: Large-scale vision-language models (VLM) such as CLIP enable strong open-vocabulary reasoning, yet deploying these capabilities on resource-constrained
arXiv:2605.05556v2 Announce Type: replace Abstract: Artificial neural networks trained on visual tasks develop internal representations resembling those of the primate visual system, a discovery that
arXiv:2609.16321v1 Announce Type: cross Abstract: Existing fairness analysis tools predominantly operate as post-training evaluation frameworks, requiring practitioners to complete the full model deve
arXiv:2609.16591v1 Announce Type: new Abstract: Traditional multimodal representation learning and generation are two stages: a contrastive or self-supervised visual encoder is trained first, followed
arXiv:2609.17210v1 Announce Type: cross Abstract: Vision-language-action (VLA) models, world-action models (WAMs), and offline reinforcement learning methods are rapidly expanding the design space of
arXiv:2609.16648v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training drives the frontier capabilities of large language models, with its wall-clock dominated by autoregressive r
arXiv:2609.16366v1 Announce Type: cross Abstract: When foundation models describe people, recent work in AI fairness, accessibility, and ethics recommends avoiding inferred identity labels (e.g., 'she
arXiv:2609.17094v1 Announce Type: new Abstract: Multimodal representation learning seeks shared representations for cross-modal retrieval and knowledge transfer. Hub-based binding reduces pairwise sup
arXiv:2609.16925v1 Announce Type: new Abstract: Hyperbolic geometry provides a natural inductive bias for genomic representation learning, but existing hyperbolic genomic models primarily use Lorentz
arXiv:2609.16811v1 Announce Type: new Abstract: Event cameras have shown great potential for robust visual perception, yet scaling event representation learning remains challenging due to the scarcity
arXiv:2609.16696v1 Announce Type: new Abstract: Autonomous excavator control is challenged by coupled kinematics, actuation lag, and uncertainty. We propose imitation learning and adaptive Cartesian t
arXiv:2609.16775v1 Announce Type: new Abstract: Annotating large radiology datasets is bottlenecked by the manual effort of delineating structures slice-by-slice in 3D volumes. Interactive methods red
arXiv:2609.17115v1 Announce Type: cross Abstract: Vision-language-action (VLA) systems already bring together two valuable resources for robot learning: rich visual representations and demonstrations