Knowledge catalogue
arXiv:2608.04425v1 Announce Type: new Abstract: Subtask labels decompose a long-horizon manipulation demonstration into shorter semantic segments for policy training and evaluation. Natural language d
arXiv:2608.05127v1 Announce Type: cross Abstract: Achieving local differential privacy in distributed optimization while maintaining low communication cost remains challenging. Existing vector quantiz
arXiv:2511.12265v2 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) remain vulnerable to diverse adversarial perturbations, motivating multi-attack adversarial training (AT) for impr
arXiv:2608.05112v1 Announce Type: cross Abstract: The Subspace Constrained Mean Shift (SCMS) algorithm is a popular nonparametric method for extracting density ridges, which serve as a low-dimensional
arXiv:2608.04934v1 Announce Type: new Abstract: Training LLM agents commonly relies on supervised fine-tuning from expert trajectories or online reinforcement learning over human-specified tasks with
arXiv:2608.04600v1 Announce Type: new Abstract: As robotic systems become increasingly complex, generating control firmware from structural description files has emerged as a promising paradigm for re
arXiv:2608.04811v1 Announce Type: new Abstract: Structured pruning enhances the efficiency of deep neural networks (DNNs) by eliminating groups of parameters during inference. Previous methods mostly
arXiv:2608.04049v1 Announce Type: cross Abstract: The principle of Occam's razor, which instructs us to prefer simplicity in inductive inference, has attracted much scrutiny both in the philosophy of
arXiv:2608.04887v1 Announce Type: new Abstract: On-policy distillation (OPD) has become an effective approach for consolidating multiple task-specialized image generation models into a single student.
arXiv:2608.05006v1 Announce Type: new Abstract: Metamodels are instrumental in reducing the computational burden associated with nested reliability analyses and optimization loops in Performance-Based
arXiv:2608.04265v1 Announce Type: cross Abstract: Evaluations of LLM planning agents largely ask whether a task succeeds or a declared plan is followed. In strategic cyber-physical systems, a stronger
arXiv:2603.03589v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) transform how machine learning (ML) pipelines are developed and evaluated. LLMs enable a new t
arXiv:2608.04904v1 Announce Type: new Abstract: Multilingual large language models exhibit substantial performance differences across languages, while existing adaptation methods often require paramet
arXiv:2608.04567v1 Announce Type: new Abstract: Event knowledge concerns who does what to whom. Psycholinguists use event-plausibility judgments to examine how this knowledge supports human language p
arXiv:2608.04309v1 Announce Type: new Abstract: We present a structured large-language-model (LLM) architecture for zero-shot human--robot coordination in a cooperative construction task with private
arXiv:2608.04149v1 Announce Type: cross Abstract: Swap regret governs the rate at which uncoupled learning dynamics converge to correlated equilibria in multiplayer general-sum games. Under full-infor
arXiv:2608.04692v1 Announce Type: cross Abstract: Task-vector arithmetic offers a closed-form way to modify a model, yet its behavioral locality remains unclear in closed-loop robot control. We presen
arXiv:2608.04676v1 Announce Type: new Abstract: Surgical procedures unfold as structured and recurring clinical events, whose real-time understanding via intraoperative surgical videos is critical for
arXiv:2608.04930v1 Announce Type: cross Abstract: Bayesian causal discovery seeks to determine the posterior distribution of causal theories, which are interpreted as directed acyclic graphs (DAGs) th
Nichiket Sunil / Reuters: Sydney-based AI data center company Firmus raised 2B in funding from Coatue, Nvidia, and others at a 10.5B post-money valuation, up from 5.5B in April — Firmus said on Friday
Taalas buried the lede for the amazing demo of their first tape out. 15k tokens per second with a llama 8b model, ability to scale that up etched onto silicon As models satisfice etching makes sense,
arXiv:2608.04043v1 Announce Type: new Abstract: Resistive pressure arrays are the cheapest and most widely shipped tactile sensors, yet tactile representation learning has concentrated on optical sens
arXiv:2608.04568v1 Announce Type: new Abstract: As a key capability for embodied intelligence, 3D visual grounding (3DVG) has been predominantly studied in indoor scenes with RGB-D or point-cloud inpu
arXiv:2608.04127v1 Announce Type: new Abstract: Large language model agents need to perceive human behavior in physical environments. Millimeter-wave (mmWave) radar provides a privacy-friendly and con
arXiv:2608.04698v1 Announce Type: cross Abstract: We tackle the challenging yet underexplored task of Generalized Referring Expression Comprehension (GREC), which requires a model to localize the obje
arXiv:2608.05138v1 Announce Type: cross Abstract: Modern Greek is absent from NVIDIA's Nemotron retrieval models and from major multilingual retrieval benchmarks, despite being important for retrieval
arXiv:2503.15560v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly vulnerable to sophisticated multi-turn manipulation attacks, where adversaries strategically build conte
As AI accelerates the speed and scale of cyberattacks, organizations are adopting AI security operations to investigate threats and respond in minutes rather than hours or days. The shift is enabling
arXiv:2604.00073v3 Announce Type: replace-cross Abstract: There has been growing interest in building agents that can interact with digital platforms to execute meaningful enterprise tasks autonomousl
arXiv:2608.04183v1 Announce Type: new Abstract: When a language model follows an in-context conditional rule such as 'if P(x) then A else B,' does it assemble a runtime circuit with one module that te
arXiv:2602.11745v2 Announce Type: replace Abstract: Graph models are fundamental to data analysis in domains rich with complex relationships. Unlike SQL, which benefits from a rel- atively unified sta
arXiv:2608.04355v1 Announce Type: new Abstract: Accuracy changes after language-model self-revision are usually interpreted as changes in reasoning. We show this can fail at the answer-extraction boun
arXiv:2608.04046v1 Announce Type: cross Abstract: Survival analysis is an established framework for analyzing time-to-event data, yet many clinical machine learning studies still binarize the outcome
I love to see these impressive models coming out that compete with the giants from companies like Z.ai, Moonshot, Alibaba, etc. A win for the open source/weight community is always welcome. While I am
arXiv:2608.05050v1 Announce Type: cross Abstract: Against the backdrop of violence in police interactions with the U.S. public, we explore how deferentially police officers speak to virtual characters
arXiv:2608.04463v1 Announce Type: new Abstract: Prior work on LLM conformity largely measures discrete answer flips under verifiable labels. Open-ended revisions require a different measurement strate
arXiv:2608.04268v1 Announce Type: new Abstract: Generative models trained on artificially generated data have been shown to exhibit model collapse, resulting in significant performance degradation. As
arXiv:2608.04589v1 Announce Type: cross Abstract: EgoCross is a cross-domain egocentric video question answering benchmark designed to evaluate whether multimodal large language models can generalize
arXiv:2608.04066v1 Announce Type: new Abstract: How do you verify a long-horizon agent when its own state and self-reports are exactly what you cannot trust? We present an agent instrument built so th
arXiv:2608.05136v1 Announce Type: new Abstract: Gradient descent on a factored model W = UV^op is implicitly biased toward low-rank solutions, while Adam, starting from the same small initialization,
arXiv:2608.04864v1 Announce Type: cross Abstract: We introduce the neural echo as a tool for understanding the behavior of neural networks. It generalizes the model-based concepts of impulse responses
The new GPT-5.6 Sol powers all chats for paid users, including Instant, creating one consistent experience. In our high-stakes factuality evaluation covering finance, medicine and law, the new GPT‑5.6
arXiv:2608.04611v1 Announce Type: cross Abstract: Frontier coding models now match or exceed strong human reference points on programming benchmarks, yet benchmark success does not imply maintainable
arXiv:2608.04570v1 Announce Type: new Abstract: Personalized LLMs with persistent memory are increasingly deployed, yet the faithfulness of their user models remains unexamined. We study over-inferenc
arXiv:2608.04432v1 Announce Type: cross Abstract: On two-sided content platforms, symmetric two-sided isolation (assigning matched fractions of creators and viewers to isolated treatment and control s
arXiv:2608.04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statis
arXiv:2608.04686v1 Announce Type: new Abstract: We study distributionally robust PAC learning for the 0--1-loss, where adversarial perturbations of the data distribution are constrained by a Cressie--
the smartest young people in sf were working on agi/alignment 5-10y ago. they are working on bci today. naomi is a total star and is one of an explosion of young talent into the bci space recently. i’
arXiv:2508.12480v3 Announce Type: replace Abstract: The ability to cooperate with unknown partners is a central challenge in cooperative AI and widely studied in the form of zero-shot coordination (ZS
Users also report that the free version was significantly downgraded after the release of the new models this is very important for us when considering local hosting. A lot of people decided not to bu
arXiv:2608.04424v1 Announce Type: new Abstract: Existing document understanding benchmarks have largely focused on locating page elements, yet real-world document intelligence requires models to reaso
This definitely seems like something worth noting, and illustrates the gap between Fable/Astra class models and the previous frontier that was 'merely' good at hacking under human instructions. Initia
This paper by researchers from MIT and Stanford finds that most people would be financially better off if they followed the financial advice of LLMs (GPT-5.2 & Gemini 3 Flash) But some people get a bi
This webinar is happening in 30 minutes, and that means there's still time to register! Following the discussion will be an open Q&A with our Head of AI Education @Prof_OZ, and the @arizeai team. See
arXiv:2608.04222v1 Announce Type: cross Abstract: Turbulence is a central testbed for machine learning on physical dynamics because its governing laws are known exactly. However, most existing studies
Together Serverless Inference gives developers a managed production path for bringing FLUX 3 into creative products and automated media workflows. Start building: https://www.together.ai/models/flux-3
arXiv:2608.04436v1 Announce Type: new Abstract: Text-to-image (T2I) models can produce visually compelling images, yet they remain limited on open-world tasks that require complex semantic understandi
arXiv:2603.18409v2 Announce Type: replace Abstract: Current document chunking methods for Retrieval-Augmented Generation (RAG) typically linearize text. This forced linearization strips away intrinsic
arXiv:2411.06024v1 Announce Type: cross Abstract: The exponential growth in protein-related databases and scientific literature, combined with increasing demands for efficient biological information r
arXiv:2601.22124v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly adapted for medical applications, but most are trained using data from a single institution because pr