All entries

arXiv:2604.16432v1 Announce Type: cross Abstract: AI in applications like screening job applicants had become widespread, and may contribute to unemployment especially among the young. Biases in the A

arXiv:2604.17842v1 Announce Type: new Abstract: LLM benchmarks are increasingly dynamic: instead of containing a fixed set of questions, they define templates and parameters that can generate an effec

AI agents are already too human. Not in the romantic sense, not because they love or fear or dream, but in the more banal and frustrating one. The current implementations keep showing their human orig

arXiv:2604.17321v1 Announce Type: new Abstract: Face morphing attacks pose a substantial risk to the reliability of face recognition systems used in passport issuance, border control, and digital iden

arXiv:2506.07826v2 Announce Type: replace Abstract: Validating autonomous driving (AD) systems requires diverse and safety-critical testing, making photorealistic virtual environments essential. Tradi

arXiv:2504.07415v2 Announce Type: replace-cross Abstract: Automated radiology report generation (RRG) holds potential to reduce the workload of radiologists, and recent advances in multimodal large la

arXiv:2510.04008v5 Announce Type: replace Abstract: Softmax Attention has a quadratic time complexity in sequence length, which becomes prohibitive to run at long contexts, even with highly optimized

arXiv:2604.16310v1 Announce Type: cross Abstract: Evaluating Retrieval-Augmented Generation (RAG) systems using static multi-turn datasets fails to capture the dynamic nature of real-world dialogues.

arXiv:2512.24086v2 Announce Type: replace Abstract: In video and image generation tasks, Diffusion Transformer (DiT) models incur extremely high computational costs due to attention mechanisms, which

arXiv:2604.18450v1 Announce Type: cross Abstract: Empirical studies of trained models often report a transient regime in which signal is detectable in a finite gradient descent time window before over

arXiv:2604.16591v1 Announce Type: new Abstract: Large language models (LLMs) sometimes memorize undesirable knowledge, which must be removed after deployment. Prior work on machine unlearning has focu

arXiv:2604.18390v1 Announce Type: new Abstract: In self-supervised learning, self-distilled methods have shown impressive performance, learning representations useful for downstream tasks and even dis

arXiv:2604.17805v1 Announce Type: new Abstract: Pairwise ranking systems based on Maximum Likelihood Estimation (MLE), such as the Bradley-Terry model, are widely used to aggregate preferences from pa

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