Knowledge catalogue
arXiv:2604.18026v1 Announce Type: new Abstract: Many deployed systems expose black-box objectives whose minimizing configuration shifts with an externally observed context. When contexts revisit a sma
arXiv:2601.22002v3 Announce Type: replace Abstract: Transformers achieve superior performance on many tasks, but impose heavy compute and memory requirements during inference. This inference can be ma
arXiv:2307.08336v2 Announce Type: replace Abstract: Despite the numerous applications of convex constraints in Robotics, enforcing them within learning-based frameworks remains an open challenge. Exis
Replit announced that app fixes and updates require developers to re-publish their applications for changes to take effect. This means that after making modifications or bug fixes to code on the Repli
arXiv:2604.17807v1 Announce Type: new Abstract: Text-to-motion (T2M) generation aims to control the behavior of a target character via textual descriptions. Leveraging text-motion paired datasets, exi
This Cursor blog post discusses best practices and strategies for improving application stability, likely covering topics such as error handling, reliability testing, monitoring, and deployment strate
arXiv:2604.17530v1 Announce Type: cross Abstract: Posture is a critical factor for beginning instrumental learners. Most students receive instruction only once a week, and during the intervals between
Real-time decisioning for AI agents requires a foundational customer context layer that provides unified, up-to-date customer data to enable accurate and personalized decisions. Databricks explains ho
arXiv:2603.19830v2 Announce Type: replace Abstract: Efficient structural perception is essential for mapping and autonomous navigation on resource-constrained robots. Existing 3D methods are computati
arXiv:2604.16587v1 Announce Type: new Abstract: We present an amortized framework for real-time visual attribution streaming in multimodal thinking models. When these models generate code from a scree
Real-World Intelligence ChatGPT Images 2.0 has an updated knowledge cutoff of December 2025 and intelligence that allows it to expertly handle tasks end-to-end, from copywriting to analysis to design
Sam Altman announced on X that OpenAI had something to reveal at 12 pm PT on a specific day, generating anticipation about an upcoming product announcement or demonstration. The post suggests a schedu
arXiv:2604.17289v1 Announce Type: new Abstract: Supervised fine-tuning of large language models relies on human-annotated data, yet annotation pipelines routinely involve multiple crowdworkers of hete
arXiv:2510.08252v2 Announce Type: replace-cross Abstract: In this paper, we introduce ReasonEmbed, a novel text embedding model developed for reasoning-intensive document retrieval. Our work includes
arXiv:2604.18307v1 Announce Type: new Abstract: Language models often solve complex tasks by generating long reasoning chains, consisting of many steps with varying importance. While some steps are cr
arXiv:2604.16565v1 Announce Type: new Abstract: While Diffusion Large Language Models (dLLMs) offer structural advantages for global planning, efficiently verifying that they arrive at correct answers
ReasoningBank is a memory framework that distills generalizable reasoning strategies from an agent's successful and failed experiences, which the agent retrieves at test time to inform interactions wh
arXiv:2604.18575v1 Announce Type: new Abstract: Story Visualization aims to generate a sequence of images that faithfully depicts a textual narrative that preserve character identity, spatial configur
Priority Technologies: Ensuring US Security and Shared ProsperityEdited by Elisabeth B. Reynolds, professor of the practice of urban studies and planning and former executive director of the MIT Task
arXiv:2604.16378v1 Announce Type: new Abstract: Large language models (LLMs) and classical machine learning methods offer complementary strengths for predictive modeling, yet their fundamentally diffe
arXiv:2604.16677v1 Announce Type: new Abstract: Vision-language-action (VLA) models have emerged as generalist robotic controllers capable of mapping visual observations and natural language instructi
arXiv:2604.17944v1 Announce Type: new Abstract: Developing agents capable of navigating fragmented, multi-source information remains challenging, primarily due to the scarcity of benchmarks reflecting
arXiv:2604.17578v1 Announce Type: new Abstract: Continual learning (CL) is concerned with learning multiple tasks sequentially without forgetting previously learned tasks. Despite substantial empirica
arXiv:2604.16734v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have recently demonstrated strong capabilities in understanding and generating responses from diverse visual in
arXiv:2604.17066v1 Announce Type: new Abstract: Coherent systems are representative of many practical applications, ranging from infrastructure networks to supply chains. Probabilistic evaluation of s
arXiv:2604.16850v1 Announce Type: new Abstract: Fast execution of contact-rich manipulation is critical for practical deployment, yet providing fast demonstrations for imitation learning (IL) remains
arXiv:2509.01082v3 Announce Type: replace Abstract: Probabilistic programming offers a powerful framework for modeling uncertainty, yet statistical model discovery in this domain entails navigating an
arXiv:2604.17800v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have gained much attention from the research community thanks to their strength in translating multimodal observat
arXiv:2511.07458v2 Announce Type: replace Abstract: Evaluating log summarization systems is challenging due to the lack of high-quality reference summaries and the limitations of existing metrics like
arXiv:2511.20233v3 Announce Type: replace Abstract: The prevalence of fake news on social media demands automated fact-checking systems to provide accurate verdicts with faithful explanations. However
arXiv:2603.05863v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have revolutionized code generation, standard ``System 1'' approaches that generate solutions in a single forward
Refocus IC LoRA is a specialized AI model addon for LTX 2.3 that uses machine learning to restore clarity to out-of-focus video footage. Created by @MedOumoumad, it integrates with the ComfyUI workflo
arXiv:2506.01770v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved tremendous success in various tasks, yet concerns about their safety and security have emerged. In
arXiv:2604.17222v1 Announce Type: new Abstract: Breast cancer diagnosis demands rapid and precise tools, yet traditional histopathological methods often fall short in intra-operative settings. Deep Ul
arXiv:2604.18145v1 Announce Type: new Abstract: Automated medical report generation for 3D PET/CT imaging is fundamentally challenged by the high-dimensional nature of volumetric data and a critical s
arXiv:2601.05053v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has proven effective in enhancing the reasoning of large language models (LLMs). Monte C
arXiv:2604.18289v1 Announce Type: cross Abstract: Autonomous swarms of multi-Unmanned Aerial Vehicle (UAV) system requires an accurate and fast relative state estimation. Although monocular frame-base
arXiv:2601.02970v2 Announce Type: replace Abstract: Self-Consistency improves reasoning reliability through multi-sample aggregation, but incurs substantial inference cost. Adaptive self-consistency m
arXiv:2604.17243v1 Announce Type: new Abstract: A robust Multimodal Large Language Model (MLLM) for Earth Observation should maintain consistent interpretation and reasoning under realistic input vari
arXiv:2601.14750v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting has achieved remarkable success in unlocking the reasoning capabilities of Large Language Models (LLMs). Although C
Replit has launched a startup program offering up to $25,000 in credits to help founders build, launch, and scale their products on the Replit platform. The program is designed for startups actively u
Meta is installing tracking software on U.S.-based employees' computers to capture mouse movements, clicks, and keystrokes for training AI models to build autonomous AI agents . The tool focuses on ar
arXiv:2604.16775v1 Announce Type: new Abstract: Every prediction from a generative medical event model is bounded by how clinical events are tokenized, yet input representation is rarely isolated from
arXiv:2604.17396v1 Announce Type: new Abstract: Large Language Models (LLMs) often memorize sensitive or harmful information, necessitating effective machine unlearning techniques. While existing para
arXiv:2604.17725v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong promise for mining Electronic Health Records (EHRs) by reasoning over longitudinal clinical information t
arXiv:2503.21248v3 Announce Type: replace Abstract: Large language models (LLMs) have shown potential in assisting scientific research, yet their ability to discover high-quality research hypotheses r
arXiv:2510.23116v3 Announce Type: replace Abstract: Diffusion bridge models establish probabilistic paths between arbitrary paired distributions and exhibit great potential for universal image restora
arXiv:2604.16925v1 Announce Type: new Abstract: Cross-dose denoising for low-dose positron emission tomography (LDPET) has been proposed to address the limited generalization of models trained at a si
arXiv:2601.18231v4 Announce Type: replace Abstract: Adapting pre-trained models to unseen feature modalities has become increasingly important due to the growing need for cross-disciplinary knowledge
arXiv:2512.12069v3 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) are vulnerable to a growing array of multimodal jailbreak attacks, necessitating defenses that are both g
arXiv:2604.17260v1 Announce Type: new Abstract: Evaluating meeting effectiveness is crucial for improving organizational productivity. Current approaches rely on post-hoc surveys that yield a single c
arXiv:2506.02541v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) can recognize individuals in images and disclose sensitive personal information about them, raising criti
arXiv:2604.17328v1 Announce Type: new Abstract: This paper investigates the length problem in sequence-level relative reinforcement learning. We observe that, although existing methods partially allev
arXiv:2412.15176v3 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly employed in real-world applications, driving the need to evaluate the trustworthiness of their generat
arXiv:2510.09351v2 Announce Type: replace Abstract: While Small Language Models (SLMs) have demonstrated promising performance on an increasingly wide array of commonsense reasoning benchmarks, curren
arXiv:2604.17898v1 Announce Type: new Abstract: With the rapid growth of video data, Composed Video Retrieval (CVR) has emerged as a novel paradigm in video retrieval and is receiving increasing atten
arXiv:2604.18112v1 Announce Type: new Abstract: In recent years, multimodal multidomain fake news detection has garnered increasing attention. Nevertheless, this direction presents two significant cha
arXiv:2604.17769v1 Announce Type: new Abstract: Ensuring the safety of large language models (LLMs) requires robust red teaming, yet the systematic synthesis of high-quality toxic data remains under-e
arXiv:2604.16593v1 Announce Type: new Abstract: We present SemanticQA, an evaluation suite designed to assess language models (LMs) in semantic phrase processing tasks. The benchmark consolidates exis
arXiv:2604.18569v1 Announce Type: cross Abstract: In this work, we revisit the problem of active sequential prediction-powered mean estimation, where at each round one must decide the query probabilit