Knowledge catalogue
arXiv:2604.08639v1 Announce Type: cross Abstract: Uncertainty quantification (UQ) is essential for deploying deep learning models in safety critical applications, yet no consensus exists on which UQ m
Boris Cherny and colleagues conducted cybersecurity evaluations of Claude Mythos Preview, finding it to be the first AI model to successfully complete an AISI (AI Safety Institute) cyber range end-to-
arXiv:2510.06499v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved remarkable success through imitation learning on vast text corpora, but this paradigm creates a tra
arXiv:2510.07517v5 Announce Type: replace Abstract: Multi-agent debate (MAD) aims to improve large language model (LLM) reasoning by letting multiple agents exchange answers and then aggregate their o
arXiv:2604.08626v1 Announce Type: new Abstract: Understanding objects in 3D from a single image is a cornerstone of spatial intelligence. A key step toward this goal is monocular 3D object detection--
arXiv:2604.08728v1 Announce Type: new Abstract: Cooperation in multi-agent reinforcement learning (MARL) benefits from inter-agent communication, yet most approaches assume idealized channels and exis
arXiv:2604.08958v1 Announce Type: cross Abstract: Reinforcement learning (RL) in robotics is often limited by the cost and risk of data collection, motivating experience transfer from a source task to
arXiv:2604.09489v1 Announce Type: cross Abstract: Model poisoning attacks pose a significant security threat to Federated Learning (FL). Most existing model poisoning attacks rely on collusion, requir
According to Waymo's published data, their technology is preventing injuries & deaths. My view is that if this is true, and I have yet to see a debunking of their data, then we safety advocates should
This r/StableDiffusion post demonstrates running AceStep 1.5 XL Turbo alongside LTX Video 2.3 on a laptop equipped with an 8GB NVIDIA RTX 5060 GPU — a notable feat given that the XL (4B) model require
Little quality of life update: Skills should be called more proactively now! ~20% more likely to load the right skill for the job! And, of course, in Hermes Agent fashion - it did the prompt improveme
MiniMax M2.7 is now available on Together AI, offering a powerful open-source model trained using a self-directed reinforcement learning loop. This training methodology enabled the model to achieve th
This r/StableDiffusion post reflects a community member reconsidering their preference between LTX (Lightricks' open-source AI video model) and daVinci-MagiHuman after peer feedback, ultimately favori
This is a discussion thread on r/MachineLearning critiquing a perceived cultural shift in AI research, where a newer wave of empirical deep learning researchers is characterized as prioritizing trendy
A lot of our education on writing well focuses on logic, clarity, and argument. AI will force us to think more about style. The boredom that comes from everything on the internet reading Claude-y now,
I am not just talking about the em-dashes and phrasing ('doing the heavy lifting'). Those are more fixable than style, which will always default to an LLM-normal even if that normal changes with new L
This r/StableDiffusion thread discusses the community debate around choosing between FLUX.2 [klein] 9B and Qwen Image Edit 2511 as an image editing model, two strong open-source contenders in the spac
arXiv:2604.06207v1 Announce Type: cross Abstract: This paper investigates demonstration selection strategies for predicting a user's next point-of-interest (POI) using large language models (LLMs), ai
arXiv:2604.07981v1 Announce Type: new Abstract: Long-context reasoning is essential for complex real-world applications, yet remains a significant challenge for Large Language Models (LLMs). Despite t
arXiv:2510.04628v2 Announce Type: replace Abstract: Deep learning-based methods have achieved significant success in remote sensing Earth observation data analysis. Numerous feature fusion techniques
arXiv:2503.17181v3 Announce Type: replace-cross Abstract: Despite the rapid progress of large language models (LLMs) in code generation, existing evaluations focus on functional correctness or syntact
arXiv:2604.08050v1 Announce Type: new Abstract: In this study, we focus on video captioning by fully open multimodal large language models (MLLMs). The comprehension of visual sequences is challenging
arXiv:2604.07665v1 Announce Type: new Abstract: Self-supervised monocular depth estimation (MDE) has received increasing interests in the last few years. The objects in the scene, including the object
arXiv:2604.06699v1 Announce Type: cross Abstract: Automated prompt optimization is crucial for eliciting reliable reasoning from large language models (LLMs), yet most API-only prompt optimizers itera
arXiv:2512.10510v2 Announce Type: replace-cross Abstract: Offline-to-Online Reinforcement Learning (O2O RL) faces a critical dilemma in balancing the use of a fixed offline dataset with newly collecte
arXiv:2604.08077v1 Announce Type: new Abstract: Processing long-form videos with Video Large Language Models (Video-LLMs) is computationally prohibitive. Current efficiency methods often compromise fi
arXiv:2512.24933v2 Announce Type: replace-cross Abstract: Multi-step LLM pipelines can solve complex tasks, but jointly optimizing prompts across steps remains challenging due to missing step-level su
arXiv:2604.06289v1 Announce Type: cross Abstract: In this paper, we analyze and improve the adversarial robustness of a convolutional neural network (CNN) that assists crystal-collimator alignment at
arXiv:2503.03088v4 Announce Type: replace-cross Abstract: The Segment Anything Model (SAM) has revolutionized image and video segmentation with its powerful zero-shot capabilities. However, its massiv
arXiv:2604.07883v1 Announce Type: cross Abstract: History textbooks often contain implicit biases, nationalist framing, and selective omissions that are difficult to audit at scale. We propose an agen
arXiv:2306.02781v4 Announce Type: replace-cross Abstract: Generative artificial intelligence, and large language models in particular, have emerged as one of the most transformative paradigms in moder
arXiv:2604.07755v1 Announce Type: new Abstract: Despite extensive research, Large Language Models continue to hallucinate when generating code, particularly when using libraries. On NL-to-code benchma
arXiv:2604.07053v2 Announce Type: replace Abstract: Recent feed-forward Gaussian reconstruction models adopt a pixel-aligned formulation that maps each 2D pixel to a 3D Gaussian, entangling Gaussian r
arXiv:2505.06182v5 Announce Type: replace-cross Abstract: Active perception is a fundamental skill that enables us humans to deal with uncertainty in our inherently partially observable environment. F
arXiv:2604.07096v1 Announce Type: new Abstract: Multi-objective bandits have attracted increasing attention because of their broad applicability and mathematical elegance, where the reward of each arm
arXiv:2511.22396v2 Announce Type: replace-cross Abstract: Recent multimodal reasoning models, inspired by DeepSeek-R1, have significantly advanced vision-language systems. However, in remote sensing (
arXiv:2604.07041v1 Announce Type: cross Abstract: Text-to-SQL is the task of translating natural language queries into executable SQL for a given database, enabling non-expert users to access structur
HappyHorse-1.0 is a pseudonymous AI video generation model that appeared on April 7, 2026, topping the Artificial Analysis Video Arena leaderboard in both text-to-video and image-to-video (no audio...
arXiv:2510.03046v2 Announce Type: replace Abstract: Machine learning potentials (MLPs) have become essential for large-scale atomistic simulations, enabling ab initio-level accuracy with computational
arXiv:2604.07306v1 Announce Type: cross Abstract: Existing dynamic data pruning methods often fail under noisy-label settings, as they typically rely on per-sample loss as the ranking criterion. This
arXiv:2604.07740v1 Announce Type: new Abstract: In recent years, video-based person Re-Identification (ReID) has gained attention for its ability to leverage spatiotemporal cues to match individuals a
arXiv:2604.06727v1 Announce Type: new Abstract: Heterogeneity in time series data is more pronounced than in vision or language, as temporal dynamics vary substantially across domains and tasks. Exist
arXiv:2604.06349v1 Announce Type: cross Abstract: Generalizing from a single labeled source domain to unseen target domains, without access to any target data during training, remains a fundamental ch
arXiv:2604.08410v1 Announce Type: new Abstract: In unstructured environments, functional dexterous grasping calls for the tight integration of semantic understanding, precise 3D functional localizatio
arXiv:2604.06323v2 Announce Type: cross Abstract: Blockchain and artificial intelligence (AI) are increasingly proposed together for securing intelligent networks, but the literature remains fragmente
arXiv:2604.07606v1 Announce Type: new Abstract: AI-driven sign language interpretation is limited by a lack of high-quality annotated data. New datasets including ASL STEM Wiki and FLEURS-ASL contain
arXiv:2601.02670v2 Announce Type: replace Abstract: We introduce self-jailbreaking, a threat model in which an aligned LLM guides its own compromise. Unlike most jailbreak techniques, which oft
arXiv:2506.12040v2 Announce Type: replace-cross Abstract: Binary quantization represents the most extreme form of compression, reducing weights to +/-1 for maximal memory and computational efficiency.
The OpenAI Academy tutorial 'ChatGPT for Customer Success Teams' covers how ChatGPT supports core customer success functions, including accelerating research, drafting communications, organizing qu...
The OpenAI Academy's 'ChatGPT for Finance Teams' tutorial teaches finance professionals how to leverage ChatGPT to streamline reporting, analyze data, improve forecasts, and communicate insights mo...
arXiv:2508.13993v2 Announce Type: replace Abstract: Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reason
arXiv:2603.20698v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in medical image analysis. However, their application in gastr
arXiv:2506.19420v2 Announce Type: replace Abstract: Multimodal sarcasm understanding is a high-order cognitive task. Although large language models (LLMs) have shown impressive performance on many dow
arXiv:2604.06468v1 Announce Type: new Abstract: Most methods for learning with noisy labels require privileged knowledge such as noise transition matrices, clean subsets or pretrained feature extracto
arXiv:2604.07484v1 Announce Type: cross Abstract: Generative reward models (GRMs) have emerged as a promising approach for aligning Large Language Models (LLMs) with human preferences by offering grea
arXiv:2604.06202v1 Announce Type: cross Abstract: Large language models (LLMs) have transformed natural language processing, yet their capabilities remain uneven across languages. Most multilingual mo
arXiv:2603.22000v2 Announce Type: replace Abstract: We propose a method for non-parametric conditional distribution estimation based on partitioning covariate-sorted observations into contiguous bins
A bug was identified in NVIDIA's cuBLAS library where `cublasSgemmStridedBatched` dispatches the same suboptimal `cutlass_80_simt_sgemm_128x32_8x5` kernel for every batched FP32 workload from 256×...
The specific Reddit thread (r/MachineLearning post ID 1shg2ob) was not returned in the search results, and I was unable to directly fetch the URL's content. I cannot accurately summarize a page I h...
arXiv:2604.07892v1 Announce Type: new Abstract: Instruction-tuned language models increasingly rely on large multi-turn dialogue corpora, but these datasets are often noisy and structurally inconsiste