Knowledge catalogue
arXiv:2604.21422v1 Announce Type: new Abstract: This paper deals with the case of using nonlinear diffusion filters to obtain piecewise constant images as a previous process for segmentation technique
arXiv:2604.21536v1 Announce Type: cross Abstract: Sequential recommender systems have achieved significant success in modeling temporal user behavior but remain limited in capturing rich user semantic
arXiv:2604.21100v1 Announce Type: new Abstract: To address the increasing long-context compute limitations of softmax attention, several subquadratic recurrent operators have been developed. This work
arXiv:2604.20899v1 Announce Type: cross Abstract: Scalable synthesis remains the gate between MOF discovery and industrial deployment, as scale-up know-how is fragmented across disparate reports. We i
arXiv:2604.21481v1 Announce Type: new Abstract: Crowdsourced pairwise evaluation has emerged as a scalable approach for assessing foundation models. However, applying it to Text to Speech(TTS) introdu
arXiv:2604.21191v1 Announce Type: new Abstract: Prefix parsing asks whether an input prefix can be extended to a complete string generated by a given grammar. In the weighted setting, it also provides
arXiv:2604.20867v1 Announce Type: cross Abstract: Recent events surrounding the relationship between frontier AI suppliers and national-security customers have made a structural problem newly visible:
arXiv:2406.11354v3 Announce Type: replace-cross Abstract: Humans can retain old knowledge while learning new information, but Large Language Models (LLMs) often suffer from catastrophic forgetting whe
We love to muse over how 'real' photography is defined here at The Verge now that generative AI is so prolific, and the World Press Photo competition might have the answer. The prestigious award celeb
arXiv:2604.21104v1 Announce Type: new Abstract: New geospatial foundation models introduce a new model architecture and pretraining dataset, often sampled using different notions of data diversity. Pe
arXiv:2604.21337v1 Announce Type: new Abstract: In this paper, we aim to extend the traditional point-mass-like robot representation in swarm robotics and instead study a swarm of long Heavy Articulat
arXiv:2106.01254v3 Announce Type: replace Abstract: In many classification tasks, there is no definitive ground truth, only human judgments that may disagree. We address two challenges that arise in s
arXiv:2604.21765v1 Announce Type: new Abstract: Data is a central resource for modern enterprises, and data validation is essential for ensuring the reliability of downstream applications. However, ex
arXiv:2604.21556v1 Announce Type: new Abstract: The problem of probabilistic verification of a neural network investigates the probability of satisfying the safe constraints in the output space when t
arXiv:2604.21811v1 Announce Type: cross Abstract: A primary goal of online deliberation platforms is to identify ideas that are broadly agreeable to a community of users through their expressed prefer
Probably the most useful advice I can give you if you run an ad agency, a marketing company, a production studio, or anything in that space. Hear me out. I’ve spent a decade talking to teams about thi
arXiv:2604.21611v1 Announce Type: cross Abstract: Inference-time scaling for LLM reasoning has focused on three axes: chain depth, sample breadth, and learned step-scorers (PRMs). We introduce a fourt
arXiv:2506.03374v2 Announce Type: replace Abstract: The use of machine learning (ML) techniques has allowed rapid advancements in many scientific and engineering fields. One of these problems is that
arXiv:2604.21041v1 Announce Type: new Abstract: Machine unlearning for text-to-image diffusion models aims to selectively remove undesirable concepts from pre-trained models without costly retraining.
arXiv:2604.21629v1 Announce Type: cross Abstract: We compare lightweight automata-based models (n-grams) with neural architectures (LSTM, Transformer) for next-activity prediction in streaming event l
arXiv:2604.21098v1 Announce Type: new Abstract: Motivated by loss of control risks from misaligned AI systems, we develop and apply methods for measuring language models' propensity for unsanctioned b
arXiv:2604.21360v1 Announce Type: new Abstract: Test-time adaptation (TTA) has emerged as a promising paradigm for vision-language models (VLMs) to bridge the distribution gap between pre-training and
Pudu Technology Inc., a leading developer of intelligent service robotics, has raised nearly 150 million in a new funding round. With this capital raise, announced Thursday, the company exceeded 1.5 b
Ben Thompson / Stratechery: Q&A with Google Cloud CEO Thomas Kurian on building infrastructure for AI agents, balancing internal needs and the demands of customers like Anthropic, and more — This week
arXiv:2604.21809v1 Announce Type: cross Abstract: Diffusion-based generative models have reformed generative AI, and have enabled new capabilities in the science domain, for example, generating 3D str
【Qwen-3.6-27B × llama.cpp】生成速度10倍の革命的スピード！ Qwen-3.6-27Bで生成速度が約10倍の136.75 t/sに到達する驚異の手法が話題です！🚀 llama.cppの「ngram-mod」という投機的デコード（Speculative Decoding）を活用。過去の出力パターンを利用して次に来る言葉を予測し、追加のビデオメモリをほぼ消費せずに高速化を実現し
arXiv:2603.27112v2 Announce Type: replace Abstract: As Automatic Train Operation (ATO) advances toward GoA4 and beyond, it increasingly depends on efficient, reliable cab-view visual perception and de
arXiv:2604.21728v1 Announce Type: new Abstract: Pretrained vision-language models such as CLIP exhibit strong zero-shot generalization but remain sensitive to distribution shifts. Test-time adaptation
ComfyUI announced a $30 million funding round to support scaling and development of its open-source node-based UI platform for AI image generation. The funding will likely be used to expand infrastruc
arXiv:2604.21357v1 Announce Type: new Abstract: This paper proposes ReaGeo, an end-to-end geocoding framework based on large language models, designed to overcome the limitations of traditional multi-
Real Human support for Seedance 2.0 is now available in ComfyUI. Unlock real human video generation with Seedance 2.0 now in ComfyUI. This unlocks real-person video generation with consistent identity
Really impressed by how smooth switching most of my coding tasks to Codex (GPT-5.5) from Claude Code (Opus 4.7) has been. I thought it was going to be more difficult and that I would be 'fighting' wit
arXiv:2604.20860v1 Announce Type: cross Abstract: Despite the success of Retrieval-Augmented Generation (RAG) in grounding LLMs with external knowledge, its application over heterogeneous sources (e.g
arXiv:2604.21249v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) enable high-level semantic reasoning for end-to-end autonomous driving, particularly in unstructured environments, e
arXiv:2604.21454v1 Announce Type: cross Abstract: Reasoning in large language models is often treated as a monolithic capability, but its observed gains may arise from more basic operations. We study
arXiv:2604.21232v1 Announce Type: new Abstract: Vision-Language-Action systems follow instructions to execute multi-step tasks in multimodal environments. Recent VLA approaches typically rely on post-
arXiv:2604.05673v2 Announce Type: replace-cross Abstract: Visual navigation is a core challenge in Embodied AI, requiring autonomous agents to translate high-dimensional sensory observations into cont
arXiv:2509.25868v3 Announce Type: replace Abstract: The mechanisms underlying scientific confabulation in Large Language Models (LLMs) remain poorly understood. We introduce ReFACT (Reddit False And C
arXiv:2604.21203v1 Announce Type: cross Abstract: We study online inference and asymptotic covariance estimation for the stochastic gradient descent (SGD) algorithm. While classical methods (such as p
🎓 Register now for ML & Advanced Stats Summer School, an intensive set of courses on theoretical foundations & applications of ML methods & modern stats analysis techniques. With @ELLISUnitMadrid. 📍 M
arXiv:2310.02635v5 Announce Type: replace-cross Abstract: Reinforcement learning (RL) is a promising approach for solving robotic manipulation tasks. However, it is challenging to apply the RL algorit
arXiv:2604.21160v1 Announce Type: new Abstract: Point-Vision-Language Models promise to empower embodied agents with executable spatial reasoning, yet they frequently succumb to geometric hallucinatio
arXiv:2604.20904v1 Announce Type: cross Abstract: Information handling practices of LLM agents are broadly misaligned with the contextual privacy expectations of their users. Contextual Integrity (CI)
arXiv:2604.21393v1 Announce Type: new Abstract: Relocation of compact sets in an n-dimensional manifold by self-diffeomorphism is of its own interest as well as significant potential applications to d
arXiv:2510.20505v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) remains brittle on multi-step questions and heterogeneous evidence sources, trading accuracy against late
I cannot provide an accurate summary for this entry as the text appears incomplete and lacks sufficient context. The post fragment references o3 (likely an AI model), GPT-5.5, and discusses timeline/e
arXiv:2604.21863v1 Announce Type: cross Abstract: Deep reinforcement learning (RL) for quantum circuit optimization faces three fundamental bottlenecks: replay buffers that ignore the reliability of t
Samsung's mobile division may record its first-ever annual loss in 2026 , driven primarily by rising memory chip prices, particularly low-power DRAM . Samsung executive TM Roh has warned that a possib
arXiv:2604.21776v1 Announce Type: new Abstract: Precise camera control for reshooting dynamic videos is bottlenecked by the severe scarcity of paired multi-view data for non-rigid scenes. We overcome
arXiv:2604.21478v1 Announce Type: new Abstract: Nowadays, visual data forgery detection plays an increasingly important role in social and economic security with the rapid development of generative mo
arXiv:2511.11439v2 Announce Type: replace-cross Abstract: Binary security has increasingly relied on deep learning to reason about malware behavior and program semantics. However, the performance ofte
arXiv:2604.21893v1 Announce Type: cross Abstract: Geographic context is often consider relevant to motor insurance risk, yet public actuarial datasets provide limited location identifiers, constrainin
arXiv:2602.03875v4 Announce Type: replace-cross Abstract: We introduce a reversible deep learning model for 13C NMR that uses a single conditional invertible neural network for both directions between
arXiv:2604.20847v1 Announce Type: cross Abstract: Music Recommendation Systems (MRSs) are a cornerstone of modern streaming platforms. Existing recommendation models, spanning both recall and ranking
arXiv:2604.21882v1 Announce Type: new Abstract: Understanding what kinds of factual knowledge large language models (LLMs) memorize is essential for evaluating their reliability and limitations. Entit
arXiv:2506.01937v2 Announce Type: replace Abstract: Reward models are used throughout the post-training of language models to capture nuanced signals from preference data and provide a training target
arXiv:2601.09253v2 Announce Type: replace-cross Abstract: While Supervised Fine-Tuning (SFT) and Rejection Sampling Fine-Tuning (RFT) are standard for LLM alignment, they either rely on costly expert
arXiv:2604.20851v1 Announce Type: cross Abstract: Modern video-text retrieval (VTR) models excel on in-distribution benchmarks but are highly vulnerable to real-world query shifts, where the distribut
arXiv:2604.21256v1 Announce Type: new Abstract: Policies for Partially Observable Markov Decision Processes (POMDPs) are often designed using a nominal system model. In practice, this model can deviat
NASA successfully rolled out the Artemis III core stage on April 20, 2026, delivering it from Michoud Assembly Facility to Kennedy Space Center . The revised mission plan calls for a crewed test in Ea