Knowledge catalogue
arXiv:2606.01597v1 Announce Type: new Abstract: Robot swarms can exhibit coherent collective behaviors through local perception, limited communication and decentralized decision-making, yet modeling a
arXiv:2408.11266v5 Announce Type: replace Abstract: Deep learning is now common across many scientific fields, including the study of partial differential equations. This article provides a brief, acc
arXiv:2602.11852v2 Announce Type: replace Abstract: While state-of-the-art language models (LMs) surpass most humans in certain domains, their reasoning remains largely opaque, reducing trust and incr
arXiv:2606.00629v1 Announce Type: cross Abstract: Sound design workflows frequently oscillate between time-consuming library searches and the complexity of procedural synthesis, with practitioners typ
arXiv:2606.00073v1 Announce Type: cross Abstract: We investigate how internal representations emerge across hierarchical processing systems by introducing a neuroscience-inspired framework for analyzi
arXiv:2604.03588v3 Announce Type: replace Abstract: AI agents operating over extended time horizons accumulate experiences that serve multiple concurrent goals, and must often maintain conflicting int
arXiv:2602.14065v2 Announce Type: replace Abstract: Knowledge-intensive Visual Question Answering (KI-VQA) frequently suffers from severe knowledge conflicts caused by the inherent limitations of open
arXiv:2510.09330v3 Announce Type: replace Abstract: Ensuring that large language models (LLMs) comply with safety requirements is a central challenge in AI deployment. Existing alignment approaches pr
arXiv:2502.07617v2 Announce Type: replace Abstract: We provide an empirical investigation of the potential of pre-training vision-language models on an unprecedented scale: 100 billion examples. We fi
arXiv:2606.01910v1 Announce Type: cross Abstract: Line drawings are a highly expressive art form that requires the artist to abstract and distill the essence of their subject. We present the first sem
arXiv:2606.00015v1 Announce Type: cross Abstract: Operating Systems (OS) courses are among the most challenging in computer science education due to the complexity of internal structures and the diver
The future of design doesn’t interrupt your process. @NousResearch Hermes keeps designers in creative flow - Rhino → ComfyUI → @Blender in one seamless agent workflow. No context switching. Just visio
arXiv:2606.00121v1 Announce Type: cross Abstract: Reconstructing visual stimuli from brain recordings has been a meaningful and challenging task in brain decoding. Especially, the achievement of preci
arXiv:2606.00046v1 Announce Type: cross Abstract: Video platforms such as YouTube have reshaped how users engage with entertainment and information, emphasizing brief, highly engaging content such as
arXiv:2606.01276v1 Announce Type: new Abstract: Large language model (LLM)-based machine translation has advanced cross-cultural communication, yet it still struggles with culture-loaded words (CLWs)
arXiv:2601.22202v2 Announce Type: replace-cross Abstract: Semantic communication (SemCom) emerges as a transformative paradigm for traffic-intensive visual data transmission, shifting focus from raw d
arXiv:2605.30667v1 Announce Type: cross Abstract: Software tools for reverse engineering executable binary files, such as Ghidra, enable malware analysts to safely conduct robust static analysis witho
arXiv:2605.31212v1 Announce Type: cross Abstract: AI systems are increasingly used to support educational content creation, yet it remains unclear whether they can generate outputs that faithfully rep
arXiv:2605.31360v1 Announce Type: cross Abstract: The Artificial Intelligence (AI) life cycle requires a thorough understanding of the underlying data dynamics for robust, safe and cost-effective AI d
arXiv:2605.30961v1 Announce Type: new Abstract: Generating novel research ideas is fundamental to scientific progress. While Large Language Models (LLMs) show promise in assisting this process, existi
arXiv:2605.31162v1 Announce Type: new Abstract: Unconditional diffusion models offer powerful generative priors, yet steering them toward aesthetically enhanced outputs remains largely unexplored. We
arXiv:2508.08204v2 Announce Type: replace-cross Abstract: There has been much recent interest in evaluating large language models for uncertainty calibration to facilitate model control and modulate u
arXiv:2605.31199v1 Announce Type: cross Abstract: Capturing dynamic malware behavior in a practical but still semantically precise manner remains a significant challenge in cyber threat intelligence.
The example of a growing restaurant Imagine you are running a restaurant chain. You just can't physically feel and touch things to know how your business operates. You need tools and a digital replica
arXiv:2605.30544v1 Announce Type: new Abstract: Visual monitoring systems that rely on cloud-based AI inference expose raw image data to external services, creating fundamental tensions with the data-
arXiv:2506.03779v2 Announce Type: replace-cross Abstract: Quantum kernel functions built using quantum-mechanical principles and have emerged as a centerpiece of quantum machine learning. The initial
arXiv:2602.12386v2 Announce Type: replace-cross Abstract: Learning stationary policies in infinite-horizon general-sum Markov games (MGs) remains a fundamental open problem in Multi-Agent Reinforcemen
arXiv:2605.31589v1 Announce Type: new Abstract: While humans naturally gesture during speech, only a sparse subset of these movements are visually depictive and semantically linked to specific spoken
I cannot provide an accurate summary of this post as the tweet content itself is not provided, only a reference indicating Jay Farei's engagement with an idea shared by Harrison Chase. Without access
arXiv:2601.09633v2 Announce Type: replace Abstract: Taxonomies form the backbone of structured knowledge representation across diverse domains, enabling applications such as e-commerce and semantic se
arXiv:2605.31245v1 Announce Type: new Abstract: Recently, sparse autoencoders (SAEs) have emerged as an attractive tool for interpreting and interacting with representations in practical neural networ
arXiv:2605.30930v1 Announce Type: cross Abstract: As large language models (LLMs) increasingly act as collaborative partners, human--AI alignment is often evaluated through explicit task success, accu
arXiv:2605.30479v1 Announce Type: new Abstract: We consider the problem of universal transductive online classification with a possibly unbounded label space. This setting considers online learning, w
arXiv:2605.31556v1 Announce Type: cross Abstract: Alignment teaches vision-language models (VLMs) to avoid expressing demographic biases, and when gender is clearly visible they largely succeed. Far l
arXiv:2605.30362v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) hold promise for demonstrating superior learning and representation capabilities in deep models. Given the tremendous s
In a way, the biggest realization AI is giving us is that we thought there was a clear line between what humans do and what the rest of physics does. AI is forcing us to confront the possibility that
This post likely argues that an individual's upbringing and early life experiences function similarly to a system prompt for an AI model—shaping foundational values, behaviors, and responses that infl
arXiv:2605.29273v1 Announce Type: new Abstract: A crucial component of machine learning algorithms is minimizing loss functions with less computational cost and less oscillations. While adaptive learn
arXiv:2603.26668v2 Announce Type: replace-cross Abstract: As an important paradigm for enhancing the generation quality of Large Language Models (LLMs), retrieval-augmented generation (RAG) faces the
arXiv:2601.21568v2 Announce Type: replace Abstract: We present a unified framework for quantifying the similarity between representations through the lens of extit{usable} information, offering a rigo
arXiv:2510.20743v2 Announce Type: replace-cross Abstract: We present Empathic Prompting, a novel framework for multimodal human-AI interaction that enriches Large Language Model (LLM) conversations wi
Many organizations’ single source of truth is data that resides in BigQuery, Google’s governed, secure and petabyte-scale data platform. However, the 'last mile' of ad-hoc analysis, modeling, and repo
arXiv:2505.21627v4 Announce Type: replace-cross Abstract: State-of-the-art large language models require specialized hardware and substantial energy to operate. As a consequence, cloud-based services
arXiv:2605.29509v1 Announce Type: new Abstract: In recent years, training-free video generation has progressed remarkably. However, when handling complex textual instructions, existing methods still s
arXiv:2605.29274v1 Announce Type: new Abstract: LLM-based automated scoring approaches near-human performance, but scaling to new tasks remains bottlenecked by the per-item human configuration of upst
arXiv:2605.30042v1 Announce Type: new Abstract: Automating scientific computing workflows requires more than generating executable code: autonomous systems must also select appropriate computational s
arXiv:2507.09574v3 Announce Type: replace-cross Abstract: Recent text-to-image models produce high-quality results but still struggle with precise visual control, balancing multimodal inputs, and requ
arXiv:2605.30187v1 Announce Type: new Abstract: The widespread adoption of AI chatbots in education will drastically change learning, making responsible deployment a critical concern. While large lang
arXiv:2605.29355v1 Announce Type: new Abstract: Understanding how cortical activity represents natural whole-body behaviors in primates remains challenging. Limited by the diversity of movements and i
arXiv:2605.28940v1 Announce Type: cross Abstract: Recently observed empirical scaling laws describe the performance of foundation-type models as three independent key quantities -- dataset size, compu
arXiv:2605.30353v1 Announce Type: new Abstract: Are AI agents tools, co-authors, or researchers? We present a quantified case study (N=1): a physicist supervising an AI coding agent (Claude Code, Sonn
arXiv:2602.06791v2 Announce Type: replace Abstract: Being probabilistic models, during inference large language models (LLMs) display rare events: behaviour that is far from typical but highly signifi
arXiv:2605.28838v1 Announce Type: cross Abstract: Extracting detailed clinical information from free-text medical narratives remains a practical challenge for researchers and healthcare systems. Termi
arXiv:2507.06092v4 Announce Type: replace-cross Abstract: Machine learning-based supervised classifiers are widely used for security tasks, and their improvement has been largely focused on algorithmi
arXiv:2601.23156v2 Announce Type: replace Abstract: We consider the problem of unsupervised skill segmentation and hierarchical structure discovery in reinforcement learning. While recent approaches h
arXiv:2605.29126v1 Announce Type: cross Abstract: A linear probe can decode a representation almost perfectly and yet be completely irrelevant to how the model uses it. On calendar-date duration reaso
Yann LeCun, a pioneering AI researcher, provides his definition of what constitutes a world model in this X post. A world model is an AI system's internal representation of how the physical world work
arXiv:2605.28615v1 Announce Type: new Abstract: Despite the rapid progress of text-to-image (T2I) models, generating images that accurately reflect complex compositional prompts (covering attribute bi
arXiv:2605.28167v1 Announce Type: new Abstract: Text-to-image diffusion models, which are theoretically equivalent to score-based generative models, generate images through a multi-step denoising proc
arXiv:2601.03549v2 Announce Type: replace-cross Abstract: Sign Language Translation (SLT) is a challenging cross-modal task requiring joint modeling of manual articulations and non-manual signals. Exi