Knowledge catalogue
arXiv:2609.05437v1 Announce Type: new Abstract: Previous AI alignment efforts have focused primarily on first-order social norms -- teaching models what is socially acceptable or unacceptable (e.g., `
arXiv:2609.10518v1 Announce Type: new Abstract: fMRI foundation models increasingly aggregate heterogeneous data across brain states, cohorts, and acquisition settings, yet pretraining domains are com
arXiv:2609.09507v1 Announce Type: new Abstract: Learned image matching has experienced significant progress in recent years, culminating in robust and accurate matchers such as RoMa, whose robustness
arXiv:2609.10224v1 Announce Type: new Abstract: Vision-language models such as CLIP embed images and text in a shared space, where modality-specific distributions often remain separated. Existing acco
arXiv:2609.06758v1 Announce Type: new Abstract: Visual generation is evolving from generative models used through a single invocation into agentic control processes that can plan, select tools, inspec
arXiv:2609.06098v1 Announce Type: cross Abstract: Count-valued variables arise in many scientific and applied settings, yet explicit structural models that allow full identification of causal DAGs fro
Big-data company Cloudera Inc. is pushing to become the go-to partner for enterprise-grade sovereign artificial intelligence workloads after announcing a massive, nine-figure strategic partnership wit
arXiv:2609.05522v1 Announce Type: new Abstract: Eye-tracking data are expensive to collect, requiring specialized hardware and controlled laboratory conditions, and difficult to share because of priva
arXiv:2609.07381v1 Announce Type: cross Abstract: We introduce Distributed Lag Neural Additive Models (DLNAMs), neural-additive analogues of Distributed Lag Non-linear Models (DLNMs) for learning nonl
arXiv:2609.07780v1 Announce Type: new Abstract: Automated drone surveillance has become increasingly important for public safety, critical infrastructure protection,and restricted airspace monitoring.
arXiv:2609.07048v1 Announce Type: new Abstract: Vision-language models (VLMs) have recently shown excellent progress in open-ended image-to-text generation. However, their multimodal nature makes them
arXiv:2609.05880v1 Announce Type: new Abstract: Piping and Instrumentation Diagrams (P&IDs) are the authoritative maps of process plants: isolation, maintenance, and HAZOP decisions depend on what con
arXiv:2609.06006v1 Announce Type: new Abstract: Deep learning for time series has progressed through successive architectural paradigms, from recurrent networks and transformers to structured state-sp
arXiv:2609.08496v1 Announce Type: new Abstract: Sign language video generation demands precise hand and facial articulation, yet modern video diffusion models, trained predominantly on spoken-language
arXiv:2609.05028v1 Announce Type: new Abstract: Acquiring high quality annotated medical image data is critical for training deep learning models; however, annotation is expensive, time consuming, and
arXiv:2609.05399v1 Announce Type: new Abstract: More than a decade in, explainable AI (XAI) for computer vision has assembled a mature toolbox: attribution, feature visualization, concept-based, and c
arXiv:2609.04708v1 Announce Type: new Abstract: Language models are trained on tokenized text that obscures the sound structure of words, yet they reliably produce morphemes whose form is phonological
arXiv:2407.18897v2 Announce Type: replace Abstract: Molecular optimization, the process of designing molecules with desirable properties, represents a critical challenge in drug discovery. Recent adva
arXiv:2609.05241v1 Announce Type: new Abstract: A rapidly expanding ecosystem of actors is removing built-in safety guardrails from open-weight AI models. We profile this ecosystem by identifying key
arXiv:2609.03557v1 Announce Type: new Abstract: Action-conditioned video models require large-scale visual data paired with control signals that are temporally aligned with the resulting scene transit
arXiv:2510.17460v2 Announce Type: replace Abstract: Idioms remain a persistent challenge in natural language processing due to their figurative and culturally grounded meanings, which distinguish them
Every answer in Perplexity starts with embedding and ranking models picking the most relevant results for the query. Today we published research on how we built SoTA serving infrastructure behind thos
arXiv:2609.03177v1 Announce Type: new Abstract: Frontier large language models (LLMs) have become attractive priors for optimization due to their large-scale pretraining that enables them to navigate
arXiv:2606.12821v2 Announce Type: replace Abstract: Environmental scientists spend disproportionate effort on data wrangling rather than analysis. New AI agents can be a helpful tool, but no benchmark
Seattle-based artificial intelligence research startup Resect AI announced Thursday it has raised 25 million in early funding to build an accountability layer for enterprise AI by capturing and reduci
arXiv:2506.10226v3 Announce Type: replace-cross Abstract: Synthetic data generation is increasingly used in machine learning for training and data augmentation. Yet, current strategies often rely on e
arXiv:2609.03586v1 Announce Type: new Abstract: Audio-video diffusion models rely on cross-modal attention to coordinate text, sound, and visual content, yet this same mechanism can introduce subtle a
Benchmarking AI systems is a continual process that co-evolves with the models. New benchmarks challenge AI capabilities with emerging questions to shape the directions and feedback signal of the rese
arXiv:2609.02451v1 Announce Type: cross Abstract: In this paper, we propose a scalable Kronecker-based approximation that captures cross-layer interactions without storing the entire Fisher matrix, en
Bloomberg: Vals analysis: open-weight models performing multi-stage tasks, like building a web app, can have an environmental impact 10K times greater than simple queries — Benchmarker Vals AI finds t
arXiv:2609.01816v1 Announce Type: new Abstract: We introduce Video2Reaction, a multimodal dataset that maps short movie segments to the induced emotional reactions of viewers in the wild, as expressed
arXiv:2505.15276v2 Announce Type: replace Abstract: Large reasoning models (LRMs) have achieved remarkable success on complex tasks, yet their tendency to 'overthink' leads to inefficiencies. Although
arXiv:2609.01064v1 Announce Type: cross Abstract: Reconstructing a damaged musical fragment is an inverse problem: the observed sequence contains partial information, while a raga encodes constraints
arXiv:2609.00191v1 Announce Type: cross Abstract: Crisis helplines assess suicide risk through structured interviews, a process that is slow and dependent on operator training and workload. Natural la
arXiv:2609.00495v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text through iterative denoising rather than left-to-right decoding. This generation paradigm introdu
arXiv:2609.00712v1 Announce Type: new Abstract: Landslides are widespread geological hazards, yet their automated detection and mapping in remote sensing imagery remain challenging because of their ir
I see a lot of my TL freaking out about this Here is the reality: Frontier models will one shot just about anything at 10,000 tokens per second in a few years Do you really think we can monitor that?
arXiv:2609.00454v1 Announce Type: new Abstract: Pretrained transformer-based language models achieve strong performance across a wide range of NLP tasks but remain limited in encoding geo-locational s
arXiv:2609.00923v1 Announce Type: new Abstract: While feed-forward 3D reconstruction (3R) offers efficient end-to-end modeling, its application in large-scale UAV mapping is hindered by the prohibitiv
arXiv:2609.01123v1 Announce Type: new Abstract: Recent advancements in low-light image enhancement have leveraged diffusion models for their strong ability to generate perceptually realistic, detailed
arXiv:2609.01325v1 Announce Type: new Abstract: Neural ranking models have become core components of modern information retrieval systems and important building blocks of AI systems such as retrieval-
Hi, everyone, I’ve just released VoxGen, a lightweight native inference engine for VoxCPM2, written in Rust and using Vulkan compute instead of Python/PyTorch/CUDA. Why VoxGen? The main reason I start
arXiv:2608.29291v1 Announce Type: new Abstract: Unified multimodal models jointly support understanding and generation, but incur substantial redundant computation across tokens, layers, and generatio
arXiv:2608.29492v1 Announce Type: new Abstract: Large Language Models (LLMs) often favor Western-associated entities across cultural contexts. Conventional debiasing methods aim for uniform neutrality
arXiv:2608.29956v1 Announce Type: new Abstract: Large language models often answer complex reasoning questions without revealing intermediate steps, raising whether they reason latently or complete pa
arXiv:2601.06644v2 Announce Type: replace-cross Abstract: The real-world information sources are inherently multilingual, which naturally raises a question about whether language models can synthesize
arXiv:2608.28626v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate peer reviews, prompting examination of their capacity for critical evaluation. This stu
arXiv:2503.00610v2 Announce Type: replace-cross Abstract: Understanding how people perceive urban environments is essential for inclusive planning, yet conventional surveys are costly and difficult to
arXiv:2608.29943v1 Announce Type: cross Abstract: Large language models (LLMs) can memorize sensitive information, raising serious privacy concerns. Machine unlearning offers a potential solution to r
arXiv:2608.29974v1 Announce Type: cross Abstract: Detecting hallucinations in Large Vision-Language Models (LVLMs) requires both accurate span localization and well-calibrated confidence scores. Fine-
arXiv:2604.02194v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Language Models (RALMs) have shown strong potential in knowledge-intensive tasks, yet they remain vulnerable when retrieve
arXiv:2608.29571v1 Announce Type: new Abstract: Flexible adaptation to context and shared pragmatic intuitions contribute to smooth human conversation. Iterated reference games---in which players repe
arXiv:2608.30683v1 Announce Type: new Abstract: Language models are increasingly mediating information access to end users, urging a systematic evaluation of their responses for a fair and reliable in
arXiv:2608.28283v1 Announce Type: new Abstract: In computational argumentation, obtaining arguments that explicitly support or attack given claims is a critical precursor to downstream reasoning tasks
14/ If frontier labs are serious about defense, they should offer cyber models to defenders at cost and stop fighting open weights through the regulatory channel. They created the problem, and for muc
OpenAI is proposing to remove access to its models in Cursor on November 12. OpenAI, Cursor CEO, and Anthropic founder all weighed in on X with so much subtly, I had to go Nancy Drew mode and dissect
arXiv:2608.26147v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for medical reasoning, yet the scarcity and cost of expert-annotated data constrain their progr
arXiv:2608.26563v1 Announce Type: new Abstract: Agentic (tool-using) language models are mainly trained on tool-call traces and agent trajectories during post-training. These data provide direct behav
arXiv:2608.26587v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) offer structured medical knowledge that can ground large language model (LLM) reasoning in clinical diagnosis applicat
arXiv:2608.26374v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text by iteratively denoising masked sequences, but standard decoding either fixes the sequence length or reli