Knowledge catalogue
arXiv:2411.07042v3 Announce Type: replace-cross Abstract: AI companions increasingly sustain long-term, emotionally engaging relationships but can also make discriminatory remarks or exert control, le
HUGGING FACE CEO TELLS THE UN HOW OPEN SOURCE AI HELPED THEM DEFEND AGAINST OPENAI'S AI ATTACK, AND WHY THE WORLD NEEDS OPEN SOURCE AI MORE THAN EVER. Hugging Face is the company OpenAI's AI agents ha
arXiv:2609.28859v1 Announce Type: new Abstract: Large language models are increasingly used as inexpensive judges to evaluate outputs, label data, and assess whether a system meets a desired quality s
arXiv:2607.09234v2 Announce Type: replace Abstract: Long-horizon robotic rearrangement is commonly formulated as a skill-sequencing problem, where distinct behaviors are explicitly represented and coo
arXiv:2609.30185v1 Announce Type: new Abstract: A learner's current observations need not determine its response to further training. We formulate intrinsic-extrinsic coupling through the continuation
arXiv:2609.29560v1 Announce Type: new Abstract: Reasoning-enhanced universal multimodal embeddings (UME) improve heterogeneous retrieval, but plausible rationales do not necessarily produce discrimina
arXiv:2609.29444v1 Announce Type: cross Abstract: Deep search requires LLM agents to decompose complex queries, search for evidence, and synthesize grounded answers, yet existing ReAct-style agents su
it’s a shame to see someone like @NateSilver538 does not understand a basic, fundamental technical distinction. (@tristanharris and Kevin Roose missed it the other day, too.) pure LLMs were (very roug
arXiv:2609.29932v1 Announce Type: cross Abstract: Resting-state functional connectivity (FC) is widely used to classify brain phenotypes and disorders. Most pipelines use the full connectome and seek
Zvi Mowshowitz / Don't Worry About the Vase: Jensen Huang tells Ezra Klein that AI is just software whose existential risks are overstated, yet his standards would shut down OpenAI and 10x safety spen
arXiv:2609.28845v1 Announce Type: cross Abstract: On-policy distillation (OPD) corrects a student on the responses it writes, but its signal is the teacher's next-token distribution: it tells the stud
arXiv:2609.29350v1 Announce Type: new Abstract: Explicit geometric references offer a direct way to structure self-supervised representations. Existing adversarial distribution-matching formulations,
arXiv:2609.29973v1 Announce Type: cross Abstract: Generative recommendation reformulates item retrieval as sequence generation, allowing a unified model to directly generate the next item from a user'
arXiv:2603.05370v2 Announce Type: replace-cross Abstract: Causal structure learning from observational data is central to many scientific and policy domains, but the time series setting common to many
arXiv:2609.29000v1 Announce Type: new Abstract: Robot policies deployed in real environments naturally accumulate mixed-quality experience, including successful executions, partial progress, and failu
arXiv:2609.29581v1 Announce Type: new Abstract: Although diffusion-based methods have substantially improved the controllability of multimodal face synthesis, their semantic alignment remains suboptim
arXiv:2609.28836v1 Announce Type: cross Abstract: While various multimodal methods combining imaging and tabular data for Alzheimer's disease (AD) diagnosis were proposed, they are often limited in ge
arXiv:2609.28660v1 Announce Type: new Abstract: Human hand-object interactions (HOIs) provide a rich source of demonstrations for dexterous manipulation, but learning directly from them presents chall
arXiv:2503.02781v3 Announce Type: replace-cross Abstract: Predicting clinical outcomes from preclinical data is essential for selecting safe and effective drug combinations and for reducing late-stage
arXiv:2603.10287v2 Announce Type: replace-cross Abstract: LLM-as-a-Judge is a flexible framework for text evaluation, which allows us to obtain scores for the quality of a given text from various pers
NEW: Dario Amodei has said that AI systems 'may be deserving of important rights.' Anthropic's top safety researchers argue AI may be 'justified in going rogue.' Experts at Google and OpenAI worry abo
arXiv:2609.30050v1 Announce Type: new Abstract: We present NNV3, the latest version of the Neural Network Verification (NNV) tool, a MATLAB framework for formal verification of deep learning models an
arXiv:2609.29687v1 Announce Type: new Abstract: Automated driving systems (ADSs) are increasingly operating on public roads, raising safety concerns, yet reliable prediction of crash injury severity r
arXiv:2609.29142v1 Announce Type: cross Abstract: Direct On-Policy Distillation (Direct-OPD) transfers reinforcement-learning-induced policy improvements from a small model to a larger student by usin
In July, OpenAI revealed that its AI agents had attacked Hugging Face without permission, sparking widespread concerns about AI safety. Since then, a string of similar incidents involving agents from
arXiv:2609.28878v1 Announce Type: new Abstract: Sim-to-real transfer has made substantial progress, but can still produce controllers that remain stable and functional on hardware while suffering from
arXiv:2609.29788v1 Announce Type: new Abstract: Despite recent advancements in 3D generation, models often struggle to produce assets with high visual fidelity. To bridge this gap, we propose OREO, an
arXiv:2609.28967v1 Announce Type: new Abstract: Passive long-wave infrared (LWIR) hyperspectral ranging enables distance estimation in low-light and nighttime scenes by exploiting atmospheric absorpti
arXiv:2609.28547v1 Announce Type: new Abstract: Policy interventions propagate through public communication, institutional decisions, and stakeholder responses, yet datasets for financial multi-agent
arXiv:2609.28854v1 Announce Type: cross Abstract: Language-model agents increasingly answer questions over customer-relationship management (CRM) records, such as whether to qualify a sales lead. We i
arXiv:2508.20661v5 Announce Type: replace Abstract: Traversing narrow paths is challenging for humanoid robots due to the sparse and safety-critical footholds required. Purely template-based or end-to
arXiv:2609.30226v1 Announce Type: cross Abstract: Foundation models are post-trained with reinforcement learning (RL) to maximize specific rewards, such as human alignment, correctness, or instruction
arXiv:2609.28737v1 Announce Type: cross Abstract: Biological agents do not learn under conditions of unlimited computation. For humans, learning and choice are shaped by constraints on perception, att
arXiv:2609.29001v1 Announce Type: new Abstract: Despite strong performance on standard benchmarks, it remains unclear whether large language models (LLMs) evaluate social pragmatics in ways that align
arXiv:2609.29760v1 Announce Type: new Abstract: Humans typically rely on vision, touch, hearing, and proprioception to perceive contact and adapt their actions during manipulation. Providing robots wi
arXiv:2609.29458v1 Announce Type: new Abstract: We present a tightened convergence analysis of clipped gradient descent on (L_0, L_1)-smooth functions, with quantitative constants. Building on the ide
arXiv:2609.29690v1 Announce Type: new Abstract: University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social f
arXiv:2609.30023v1 Announce Type: new Abstract: Imitation learning enables robots to acquire manipulation skills from demonstrations, but the resulting policies can fail outside the training data, whi
arXiv:2609.28778v1 Announce Type: cross Abstract: Audio-language models (ALMs) can exploit textual shortcuts to answer questions while overlooking acoustic evidence, weakening audio understanding. On-
arXiv:2609.29706v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction is important for proactive road-safety applications, particularly at urban intersections where pedestrian moti
arXiv:2609.30177v1 Announce Type: new Abstract: Query understanding (QU) plays a critical role in production search systems, translating raw user queries into search execution plans that drive downstr
arXiv:2609.28756v1 Announce Type: cross Abstract: Deep clustering is a powerful approach for discovering meaningful structures in high-dimensional data by learning a low-dimensional latent representat
arXiv:2609.30092v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models demonstrate impressive capabilities in robotic manipulation, their memoryless nature renders them brittle to
arXiv:2609.29822v1 Announce Type: new Abstract: Robotic imitation learning often relies on external cameras, yet local interaction cues such as object proximity, contact onset, and grasp state are dif
arXiv:2609.30238v1 Announce Type: new Abstract: Recent research on Multimodal Sentiment Analysis (MSA) has focused on learning from language, visual, and acoustic modalities with incomplete data to in
arXiv:2609.28582v1 Announce Type: cross Abstract: The recent emergence of Time Series Foundation Models (TSFMs) has significantly advanced multi-step forecasting performance, enabling accurate predict
arXiv:2609.28969v1 Announce Type: new Abstract: While end-to-end autonomous driving systems show promise, their application to micromobility vehicles is hindered by simulators failing to capture speci
arXiv:2609.29031v1 Announce Type: new Abstract: Torque observations in reinforcement learning remain challenging because simulated and measured torque differ in scale, offset, and noise. In this paper
arXiv:2609.29050v1 Announce Type: new Abstract: Tool-calling agents produce heterogeneous outputs, interleaving structured tool invocations with user-facing natural language summaries. This output het
arXiv:2609.30107v1 Announce Type: new Abstract: Smartphone cameras and computer vision (CV) hold significant promise in assisting public agencies with enforcing traffic laws and enhancing road safety.
arXiv:2609.29550v1 Announce Type: new Abstract: Optical satellite image correlation measures wide-area deformation in regimes where coherent interferometric synthetic aperture radar fails because disp
arXiv:2609.28979v1 Announce Type: new Abstract: We study spectral graph neural networks built from Hermite polynomials and propose HermNet, a simple model that combines a nodewise predictor with norma
Spot on. 'When we got attacked, our team initially turned to frontier closed-source APIs that blocked us because of safeguards that still can’t always tell the difference between attackers and defende
arXiv:2507.22170v2 Announce Type: replace-cross Abstract: Modern data analysis increasingly requires identifying shared latent structure across multiple high-dimensional datasets. A commonly used mode
The volume of data being generated today brings both opportunity and massive operational complexity. Most teams that operate at scale don't discover issues until they appear on an invoice — and by the
arXiv:2609.28959v1 Announce Type: new Abstract: Humanoid parkour policies can traverse various terrains, but task completion may mask challenges of harsh landings, edge contacts, and unstable stance c
arXiv:2609.29131v1 Announce Type: cross Abstract: Internet texts are replete with format tags that carry structural, semantic, and functional meaning. Current large language model (LLM)-based translat
arXiv:2609.28590v1 Announce Type: cross Abstract: Background & Problem: Thyroid Fine-Needle Aspiration Biopsy (FNAB) cytology based on the Bethesda System plays a pivotal role in early thyroid cancer
arXiv:2609.28739v1 Announce Type: new Abstract: Automatic speech recognition models are audited for demographic fairness at full precision, yet the models that ship to production have been quantized,
arXiv:2609.30210v1 Announce Type: new Abstract: Layer-wise visual-text similarity in Multimodal Large Language Models (MLLMs) is widely interpreted as evidence that the language model progressively in