Knowledge catalogue
arXiv:2605.00721v1 Announce Type: cross Abstract: The Room Acoustics and Speaker Distance Estimation (SDE) Challenge at ICASSP 2025 explores the effectiveness of augmented room impulse response (RIR)
arXiv:2603.20999v2 Announce Type: replace-cross Abstract: Adaptive 360{eg} video streaming for teleoperation faces two coupled challenges: viewport prediction under uncertain gaze patterns and bitrate
arXiv:2605.01928v1 Announce Type: new Abstract: Neural networks increasingly embed non-differentiable components (spiking neurons, quantized layers, discrete routing, blackbox simulators, etc.) where
arXiv:2605.01761v1 Announce Type: new Abstract: Text-to-Video (T2V) models have demonstrated remarkable capability in generating temporally coherent videos from natural language prompts, yet they also
arXiv:2605.01950v1 Announce Type: new Abstract: World models enable long-horizon planning by internally generating and evaluating imagined trajectories, making them a promising foundation for generali
arXiv:2605.00224v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human preferences is commonly done via reinforcement learning from human feedback (RLHF) with Proximal Policy
arXiv:2602.07784v3 Announce Type: replace Abstract: Camera-based adaptive traffic signal control is inherently partially observable: detections can be missed, vehicle speeds and distances can be noisy
arXiv:2605.02126v1 Announce Type: new Abstract: Ultrasound foundation models have achieved strong performance on structured prediction tasks but remain exclusively vision-based, limiting zero-shot and
arXiv:2208.01899v2 Announce Type: replace Abstract: Imitation learning learns a policy from expert trajectories. While the expert data is believed to be crucial for imitation quality, it was found tha
arXiv:2605.02762v1 Announce Type: new Abstract: Online mapping and end-to-end (E2E) planning in autonomous driving remain largely sensor-centric, leaving rich map priors, including HD/SD vector maps,
arXiv:2605.02884v1 Announce Type: new Abstract: Ensuring the coherence of regional socio-economic statistics is a central task for national statistical institutes. Traditional validation tools, such a
New York Times: US labor experts and economists warn US unemployment benefits are unlikely to protect against AI job losses, and the GOP-led Congress is doing little to prepare — Economists aren't sur
arXiv:2605.01051v1 Announce Type: cross Abstract: While Bellman equations for basic reach, avoid, and reach-avoid problems are well studied, the relationship between value optimality and policy optima
arXiv:2601.23286v2 Announce Type: replace Abstract: While recent video diffusion models (VDMs) produce visually impressive results, they fundamentally struggle to maintain 3D structural consistency, o
arXiv:2605.01101v1 Announce Type: cross Abstract: This paper develops Virtual Speech Therapist (VST), an intelligent agent-based platform that streamlines stuttering assessment and delivers customized
arXiv:2605.02487v1 Announce Type: new Abstract: This paper addresses the problem of mobile grasping in dynamic, unknown environments where a robot must operate under a limited field-of-view. The funda
arXiv:2605.01518v1 Announce Type: new Abstract: The ability to push large objects in a goal-directed manner using onboard egocentric perception is an essential skill for humanoid robots to perform com
Gary Marcus critiques the gap between AI aspirations and current reality, suggesting that instead of achieving transformative 'singularity' breakthroughs, AI development has become cyclical—repeating
arXiv:2605.02323v1 Announce Type: new Abstract: Compositional inference - the decomposition of observations into an unknown number of latent components - is central to perception and scientific data a
arXiv:2605.01133v1 Announce Type: cross Abstract: Large language model (LLM)-powered multi-agent systems (MAS) enable agents to communicate and share information, achieving strong performance on compl
While AI leaders warn superintelligent AI could cause human extinction, governments are asleep at the wheel. The companies building superintelligence admit the danger, yet expect to create the tech wi
arXiv:2605.01416v1 Announce Type: cross Abstract: The increasing scale and complexity of online platforms raises critical policy questions around harmful content, digital well-being, and user autonomy
arXiv:2505.13150v2 Announce Type: replace Abstract: Behavioral Foundation Models (BFMs) proved successful in producing policies for arbitrary tasks in a zero-shot manner, requiring no test-time traini
arXiv:2605.01787v1 Announce Type: cross Abstract: Autonomous navigation and obstacle avoidance remain a core challenge of modern Unmanned Aerial Vehicles (UAVs). While traditional control methods stru
arXiv:2508.11696v3 Announce Type: replace Abstract: A deep learning real-time smoking detection system for CCTV surveillance of fire exit areas is proposed due to critical safety requirements. The dat
arXiv:2605.00457v1 Announce Type: cross Abstract: The coexistence of NR-U and Wi-Fi in unlicensed spectrum introduces a system-level resource coordination problem, where heterogeneous channel access m
Gary Marcus explores hypothetical scenarios and consequences if OpenAI were to fail or lose its competitive position in the AI industry. The post likely examines implications for AI development, the b
arXiv:2605.00229v1 Announce Type: cross Abstract: We study the problem of training diffusion and flow generative models to sample from target distributions defined by an exponential tilting of a base
arXiv:2605.00443v1 Announce Type: cross Abstract: The advancement of generalized deepfake disruption is constrained by the interruption imbalance, a fundamental bottleneck inherent to the generation o
arXiv:2605.00410v1 Announce Type: new Abstract: A multi-agent pipeline with N agents typically issues N LLM calls per run. Merging agents into fewer calls (compound execution) promises token savings,
Almost every warning that I have issued over the last several years has come true. You better hope to God or Darwin or whoever you believe in that this one is wrong. Accidental nuclear war is a potent
🌐At the @UN, @Yoshua_Bengio briefed @antonioguterres on AI governance, followed by a reception with @CanadaUN & @DavidLametti opened by @EgriseldaL As AI risks grow, global coordination matters. 🔗AI D
arXiv:2605.00667v1 Announce Type: new Abstract: Safety is a primary challenge in real-world reinforcement learning (RL). Formulating safety requirements as state-wise constraints has become a prominen
arXiv:2508.06361v4 Announce Type: replace Abstract: Large Language Models (LLMs) are widely deployed in reasoning, planning, and decision-making tasks, making their trustworthiness critical. A signifi
arXiv:2602.03265v2 Announce Type: replace Abstract: Large Language Models (LLMs) have seen widespread adoption across multiple domains, creating an urgent need for robust safety alignment mechanisms.
arXiv:2411.10915v2 Announce Type: replace Abstract: Large Language Models (LLMs) have revolutionized natural language processing, but their susceptibility to biases poses significant challenges. This
arXiv:2605.00632v1 Announce Type: new Abstract: Automatic generation of executable Blender code from natural language remains challenging, with state-of-the-art LLMs producing frequent syntactic error
arXiv:2605.00405v1 Announce Type: new Abstract: Most existing heterogeneous cooperative perception methods depend on prior preparation like offline joint training or tailored collaborator-model adapta
arXiv:2602.00665v3 Announce Type: replace Abstract: Customer-service question answering (QA) systems increasingly rely on conversational language understanding. While Large Language Models (LLMs) achi
Confirmed 2.5 years later, by Greg Brockman. Remember how Sam Altman told the US Senate he had no “direct” investment in OpenAI? and how they gushed over his apparent selflessness? 👉He didn’t mention
arXiv:2605.00330v1 Announce Type: new Abstract: Operator learning enables fast surrogate modeling of high-dimensional dynamical systems, but existing approaches face two fundamental limitations: quadr
arXiv:2605.00298v1 Announce Type: new Abstract: Deploying reinforcement learning policies in the real world requires adapting to time-varying environments. We study this problem in the contextual Mark
arXiv:2512.20260v5 Announce Type: replace Abstract: Weakly-Supervised Camouflaged Object Detection (WSCOD) aims to locate and segment objects that are visually concealed within their surrounding scene
arXiv:2605.00723v1 Announce Type: cross Abstract: We propose Decentralized Proximal Stochastic Gradient Langevin Dynamics (DE-PSGLD), a decentralized Markov chain Monte Carlo (MCMC) algorithm for samp
arXiv:2506.00166v2 Announce Type: replace-cross Abstract: Existing paradigms for ensuring AI safety, such as guardrail models and alignment training, often compromise either inference efficiency or de
Gary Marcus and Sam Altman testified before the Senate regarding AI oversight, with Marcus noting that two individuals stood up during the hearing and asserting that one of them told the truth. This r
arXiv:2605.00059v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) finds extensive application in autonomous drone navigation within complex, high-risk environments. However, its practi
arXiv:2605.00238v1 Announce Type: new Abstract: Automated short answer grading (ASAG) with large language models (LLMs) is commonly evaluated with aggregate metrics such as macro-F1 and Cohen's kappa.
arXiv:2605.00012v1 Announce Type: cross Abstract: Modern large language models (LLMs) are used in many business applications in general, and specifically in web search systems and applications that ge
arXiv:2605.00185v1 Announce Type: new Abstract: Dataset Distillation aims to compress a large dataset into a small synthetic one while maintaining predictive performance. We show that as different dem
arXiv:2605.00592v1 Announce Type: new Abstract: In Machine Learning, an accepted definition of fairness of a decision taken by a classifier is that it should not depend on protected features, such as
arXiv:2605.00678v1 Announce Type: new Abstract: Aerosol Optical Depth (AOD) retrieval is essential for Earth observation, supporting applications from air quality monitoring to climate studies. Conven
arXiv:2509.24621v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are emerging as versatile foundations for mixed-modality retrieval. Yet, they often require heavy post-hoc
Gary Marcus criticizes overhyped AI claims, with the term 'marcussed' referring to his practice of debunking exaggerated AI assertions. The post appears to reference a discussion with Yann LeCun about
🚨 GREG BROCKMAN JUST CONFESSED UNDER OATH Q: You have an ownership interest in this cap profit company. Brockman: That is accurate. Q: And you invested 0 in order to acquire that interest. Correct? Br
Greg Brockman’s diary is well on its way to being the most famous, impactful diary of the 21st century. takeaway from Greg Brockman testimony at Elon vs. OpenAI trial today is that no grown man should
Hey filthy rich AI warlords who have alienated most of the population, don’t say I didn’t try to warn you.🤷♂️ “Bubble or not, the AI backlash is validating what one researcher and critic has been say
Ellen Cushing / The Atlantic: How “emotion AI”, the use of facial and sentiment analysis tools to track workers' moods, is seeping into white-collar jobs amid concerns over privacy and bias — The good
arXiv:2605.00269v1 Announce Type: new Abstract: Recent white-box OOD detection methods for LLMs -- including CED, RAUQ, and WildGuard confidence scores -- appear effective, but we show they are struct
arXiv:2605.00820v1 Announce Type: cross Abstract: We introduce HyCOP, a modular framework that learns parametric PDE solution operators by composing simple modules (advection, diffusion, learned closu