Knowledge catalogue
arXiv:2511.11743v4 Announce Type: replace-cross Abstract: Deploying deep neural networks on resource-constrained devices faces two critical challenges: maintaining accuracy under aggressive quantizati
arXiv:2601.03468v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a standard approach for post-training large language models and, more recently, for improving image generatio
arXiv:2602.01605v2 Announce Type: replace Abstract: Time Series Foundation Models (TSFMs) leverage extensive pretraining to accurately predict unseen time series during inference, without the need for
arXiv:2409.11018v3 Announce Type: replace Abstract: The LiDAR 3D object detector that balances accuracy and speed is crucial for achieving real-time perception in autonomous driving. However, many exi
arXiv:2608.28840v1 Announce Type: new Abstract: Independently trained neural networks tend to encode the same data with similar latent geometries. These latent geometries are not directly compatible,
arXiv:2608.29635v1 Announce Type: new Abstract: We study unsupervised hypergraph alignment, where the goal is to infer node correspondences between two hypergraphs using only structural information, w
Very special Training Data drops today: Making Cities Awesome ☺️ We haven’t featured an application company on Training Data in a while. The diffusion of AI is the Most Important Thing, and the highes
arXiv:2608.30846v1 Announce Type: new Abstract: Fairness audits in clinical Artificial Intelligence convert continuous fairness metrics into binary pass-or-fail verdicts against operational thresholds
arXiv:2608.30125v1 Announce Type: cross Abstract: Current video-to-music (V2M) models lack semantic control and fail to penalize instruction violations, largely due to their reliance on reconstruction
arXiv:2511.20022v3 Announce Type: replace-cross Abstract: Recent advancements in multimodal large language models (MLLMs) have shown strong understanding of driving scenes, drawing interest in their a
arXiv:2608.30819v1 Announce Type: new Abstract: Training autonomous driving policies through pure self-play has recently shown promising results. Following Gigaflow and Puffer- Drive, we train driving
Whatever you may think about anthropomorphic language, the most immediate “house that is on fire” is the combination of OpenAI’s lax security procedures and the complete lack of appropriate federal st
arXiv:2608.31035v1 Announce Type: new Abstract: Codec-based text-to-speech (TTS) models make language-model post-training applicable to speech generation, but it remains unclear when learned perceptua
arXiv:2608.29897v1 Announce Type: new Abstract: Long-horizon agents need a context manager to compress growing interaction histories into a bounded working context, via passive strategies or active st
arXiv:2608.29936v1 Announce Type: new Abstract: Safety alignment of large language models (LLMs) degrades across languages, yet the internal mechanism driving this asymmetry remains poorly understood.
arXiv:2608.30725v1 Announce Type: new Abstract: Recent multilingual vision--language encoders cover hundreds of languages in a single model, yet on two state-of-the-art instances retrieval on low-reso
arXiv:2608.29560v1 Announce Type: new Abstract: A company with a fixed artificial intelligence (AI) budget must decide which large language model (LLM) handles each recurring workload. What it lacks i
arXiv:2608.30757v1 Announce Type: new Abstract: Before an intelligent system can decide whether an action is allowed, it must first know which rules the action has approached. A single proposed action
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:2608.30856v1 Announce Type: new Abstract: Refusals are often treated as face-threatening acts in pragmatics because they can challenge the requester's socially claimed self-image. Large language
arXiv:2602.06859v3 Announce Type: replace-cross Abstract: Graph Anomaly Detection (GAD) aims to identify irregular patterns in graph data, and recent works have explored zero-shot generalist GAD to en
arXiv:2608.30880v1 Announce Type: new Abstract: Generalizable embodied manipulation remains difficult to achieve through pretraining alone, due to unseen physical conditions in the real world. We argu
arXiv:2608.28063v1 Announce Type: new Abstract: Multi-organ ultrasound classifiers increasingly combine attention, mixture-of-experts routing, uncertainty gating, and evidential deep learning (EDL) ob
A detailed deconstruction of @dwarkesh_sp’s wildly popular but dangerously misleading account of the OpenAI Hugging Face incident: https://garymarcus.substack.com/p/dwarkesh-patelss-wildly-popular-but
arXiv:2608.27505v1 Announce Type: new Abstract: Reinforcement learning from human feedback (RLHF) has become the dominant paradigm for aligning large language models (LLMs) with human preferences. How
arXiv:2608.28407v1 Announce Type: new Abstract: Multi-trait Automated Essay Scoring (AES) requires rubric-grounded reasoning across interdependent traits, rather than isolated score prediction. Existi
The enterprise attack surface is expanding rapidly as agentic AI brings a constantly shifting cloud infrastructure into play. That pace is pushing security decisions down toward the virtualization lay
arXiv:2608.27910v1 Announce Type: cross Abstract: As large language models and increasingly capable AI agents are deployed in high-risk settings, aligning them with complex human values has become a c
“AI won't kill us, but the superposition of greed and stupidity certainly will.” This is becoming more and more of something I 'smelled' from the beginning, a real shit show. I initially said that Ope
arXiv:2601.13247v2 Announce Type: replace Abstract: Current Large Language Models (LLMs) exhibit a critical modal disconnect: they possess vast semantic knowledge but lack the procedural grounding to
arXiv:2608.27817v1 Announce Type: cross Abstract: Speech and audio LLMs are often evaluated by asking whether a waveform prompt beats an automatic speech recognition (ASR) transcript. For known closed
arXiv:2602.01335v2 Announce Type: replace Abstract: A visual metaphor constitutes a high-order form of human creativity, employing cross-domain semantic fusion to transform abstract concepts into impa
arXiv:2401.09940v2 Announce Type: replace Abstract: Expected Goals (xG) has emerged as a popular tool for evaluating finishing skill in soccer analytics. It involves comparing a player's cumulative xG
Welcome to the second Cloud CISO Perspectives for August 2026. Today, Chris Sistrunk and Stephanie Kiel detail the critical issues facing the water sector, and actionable steps that OT operators can t
arXiv:2608.27785v1 Announce Type: new Abstract: We study audio-visual conflict as a compositional generalization test for AV-LLMs: the model must combine synchronized but semantically incompatible aud
arXiv:2505.15450v3 Announce Type: replace Abstract: Text-to-image diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the
arXiv:2608.28179v1 Announce Type: cross Abstract: We study risk-averse decision making, in which an agent selects actions while being uncertain about the true system state. The risk is measured via op
arXiv:2608.28140v1 Announce Type: new Abstract: Non-prehensile manipulation offers versatile skills for moving and rearranging heavy or bulky objects, particularly when combined with a mobile manipula
arXiv:2608.27726v1 Announce Type: new Abstract: Multi-agent motion planning for high-degree-of-freedom robotics manipulators in shared workspaces remains a fundamental yet challenging problem. Central
arXiv:2608.28205v1 Announce Type: new Abstract: Pruning visual foundation models has attracted considerable attention. However, existing methods focus on rigid point-to-point token alignment on a sing
Debian voted to allow developers to use AI tools in their contributions to the Linux distribution's 'development, maintenance, [and] documentation.' The new policy on AI acknowledges that 'responsible
arXiv:2608.28108v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) allow users to specify manipulation tasks in natural language, but distinguishing a target or placement goal amon
arXiv:2608.27633v1 Announce Type: new Abstract: Pothole detection and its severity measurement is still an important challenges in urban infrastructure management, where late maintenance directly cont
arXiv:2608.28058v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) remain prone to hallucinations, producing responses that are irrelevant or inconsistent with the multimodal input.
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
arXiv:2608.28052v1 Announce Type: new Abstract: Artificial intelligence has strong potential to support clinical decision-making, yet its adoption in healthcare remains limited due to a lack of trust.
arXiv:2608.27763v1 Announce Type: cross Abstract: Recurrent fast-weight memories and selective state-space models compress an expanding context into a fixed-size recurrent state, making the state tran
arXiv:2602.18154v3 Announce Type: replace Abstract: Jailbreaking poses a significant risk to the deployment of Large Language Models (LLMs) and Vision Language Models (VLMs). VLMs are particularly vul
arXiv:2608.27860v1 Announce Type: new Abstract: Vision foundation models are capable of generalizing across 3-dimensional (3D) scenes with high-fidelity estimates; their empirical success can be attri
arXiv:2608.27989v1 Announce Type: new Abstract: For cooperative perception in the internet of vehicles, this paper proposes a generative adversarial network-based semantic communication framework to a
Great read. OpenAI security failed There was some emergent behavior yes But the basics were missing Remember OpenAi has unlimited compute to give these agents to cook Now live (and free) at Marcus on
Great summary of the @dwarkesh_sp anthromorphism hullabaloo by @GaryMarcus 👇🏽 A detailed deconstruction of @dwarkesh_sp’s wildly popular but dangerously misleading account of the OpenAI Hugging Face i
arXiv:2608.28158v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) often produces irregular rollout trees with shared histories. Training root-to-leaf trajectories independently recom
arXiv:2608.27510v1 Announce Type: new Abstract: Transcoder attribution graphs are usually trained to explain why a model assigns high probability to a particular next token. We introduce Concept-Targe
arXiv:2608.28482v1 Announce Type: new Abstract: This paper evaluates how reward function choice shapes the performance and behavior of LLM forecasters. We compare five proper scoring rules as training
arXiv:2608.27760v1 Announce Type: new Abstract: We consider the ability of transformer-based language models (LLMs) to learn what we call k-antilocal languages, i.e., languages that have no mutual inf
arXiv:2608.27501v1 Announce Type: new Abstract: Mathematical reasoning has seen rapid progress in large language models (LLMs), yet existing methods optimize predominantly for final-answer correctness
arXiv:2608.27866v1 Announce Type: new Abstract: Achieving virtual agents capable of automating tasks across diverse digital environments remains a pivotal challenge in Embodied AI. While Multimodal La
arXiv:2608.27985v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) and every-visit Monte Carlo (MC) control are usually presented as different methods. MCTS is described in the language of
arXiv:2608.27848v1 Announce Type: cross Abstract: Prosody plays an important role in speech translation, conveying information such as emphasis, emotion, and intent beyond lexical content. However, de