Knowledge catalogue
arXiv:2605.21422v1 Announce Type: new Abstract: As LLMs continue to scale, improving training efficiency increasingly depends on using data more effectively. Data selection addresses this problem by a
arXiv:2605.21225v1 Announce Type: new Abstract: We address the problem of making a pre-trained reinforcement learning (RL) policy safety-aware by incorporating cost constraints without retraining it f
arXiv:2603.10726v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) rely on optimizations like Automatic Prefix Caching (APC) to accelerate inference. APC works by reusing previousl
arXiv:2605.20961v1 Announce Type: new Abstract: Existing 4D-driven video diffusion models primarily target plausible generation, but faithful 4D editing requires preserving source-observed regions whi
Pretty profound for an ipo filing: “For the entirety of its existence, human civilization has lived on a single celestial body: Earth. The current paradigm, in which human civilization is confined to
arXiv:2510.21583v2 Announce Type: replace Abstract: Recent Progress in post-training flow matching for text-to-image (T2I) generation with Group Relative Policy Optimization (GRPO) has demonstrated st
arXiv:2605.20245v1 Announce Type: cross Abstract: We introduce extbf{Prism}, a framework for structural symmetry diagnosis in complex networks. Given a graph Laplacian L and a duality operator P (a sy
arXiv:2605.20867v1 Announce Type: cross Abstract: Multimodal sarcasm detection requires reasoning over cross-modal incongruities between literal expression and intended meaning, yet the specific analy
arXiv:2602.06886v3 Announce Type: replace Abstract: Multimodal Diffusion Transformers (MMDiTs) for text-to-image generation maintain separate text and image branches, with bidirectional information fl
proof too complicated, Claude help ELI5 Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in 1946. For nearly 80 years, mathematician
arXiv:2605.21454v1 Announce Type: new Abstract: We introduce ProtoPathway, an interpretable-by-design multimodal framework for cancer survival prediction that unifies whole slide imaging and transcrip
arXiv:2605.20235v1 Announce Type: new Abstract: Diffusion models generate high-dimensional data with remarkable quality, yet how their training efficiently learns the score function, bypassing the cur
arXiv:2605.20355v1 Announce Type: cross Abstract: Skill atrophy, the gradual decline of human capability under AI assistance, poses a safety risk in shared-control of semi-autonomous systems, where op
arXiv:2605.20531v1 Announce Type: cross Abstract: Reliable verification of proofs remains a bottleneck for training and evaluating AI systems on hard mathematical reasoning. Fully formal proofs, in la
arXiv:2605.20195v1 Announce Type: new Abstract: A target-oriented proactive dialogue system is designed to steer conversations toward predefined targets while actively providing suggestions. The core
The Vercel CLI now supports pulling anomaly alert details, allowing developers to programmatically access information about performance anomalies detected in their deployments. This feature enables in
arXiv:2605.20813v1 Announce Type: new Abstract: Inference in diffusion large language models (dLLMs) is computationally expensive, as full self-attention must be repeatedly executed at each step of th
arXiv:2605.20404v1 Announce Type: new Abstract: The rapid adoption of Generative AI, including LLM-based chatbots like ChatGPT, has highlighted the need for accessible ways to support public understan
arXiv:2605.21072v1 Announce Type: new Abstract: Autoregressive video diffusion models (ARVDs) have emerged as a promising architecture for streaming video generation, paving the way for real-time inte
arXiv:2602.01273v4 Announce Type: replace Abstract: Recently, Diffusion Transformers (DiTs) have emerged in Real-World Image Super-Resolution (Real-ISR) to generate high-quality textures, yet their he
arXiv:2509.24725v3 Announce Type: replace Abstract: Estimating queue lengths at signalized intersections is a long-standing challenge in traffic management. Partial observability of vehicle flows comp
arXiv:2605.20801v1 Announce Type: new Abstract: Adaptive robot navigation in dynamic environments requires policies that can reach the target reliably while producing efficient and stable trajectories
arXiv:2605.21164v1 Announce Type: new Abstract: Credit card fraud detection is fundamentally challenged by extreme class imbalance, where fraudulent transactions are rare yet operationally critical. T
arXiv:2605.20482v1 Announce Type: new Abstract: Quadratic constraints (QCs) are widely used to characterize nonlinearities and uncertainties, but generic analytical characterizations can be conservati
arXiv:2605.21486v1 Announce Type: new Abstract: Hyperparameter transfer allows extrapolating optimal optimization hyperparameters from small to large scales, making it critical for training large lang
arXiv:2605.21403v1 Announce Type: new Abstract: Agreement attraction errors, in which a verb erroneously agrees with an intervening noun rather than its grammatical head, are amplified by morphologica
arXiv:2605.20295v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed on mobile devices, where Neural Processing Units (NPUs) necessitate fully static quantization for
arXiv:2605.20222v1 Announce Type: cross Abstract: Contextual combinatorial optimization (CCO) plays a critical role in decision-making under uncertainty, yet remains a significant challenge. We presen
arXiv:2510.00171v2 Announce Type: replace-cross Abstract: We investigate quantum reservoir computing (QRC) using a hybrid qubit-boson system described by the Jaynes-Cummings (JC) Hamiltonian and its d
arXiv:2512.09447v2 Announce Type: replace-cross Abstract: Structurally repetitive environments produce visually plausible but aliased LiDAR loop candidates that can destabilize pose-graph optimization
Vercel has announced the availability of Qwen 3.7 Max, a language model, through its Vercel AI Gateway platform. This integration allows developers to access and use Qwen 3.7 Max alongside other AI mo
🚀Qwen3.7-Max just landed at 56.6 on the Artificial Analysis Intelligence Index — a solid 4.8pt jump over Qwen3.6-Max-Preview. @ArtificialAnlys ⚡️Sharper sci reasoning, stronger agentic chops, better c
arXiv:2605.20584v1 Announce Type: new Abstract: Mobile app marketplaces require developers to disclose standardized content rating descriptors (CRDs) to inform users about potentially sensitive or res
arXiv:2605.21099v1 Announce Type: new Abstract: Accurate estimation of the Angle of Progression (AoP) from intrapartum transperineal ultrasound is critical for objective assessment of labor progressio
arXiv:2508.03578v2 Announce Type: replace Abstract: Radar-based human pose estimation enables privacy-preserving motion tracking for ambient intelligence, yet the noisy nature of radar sensing makes u
arXiv:2605.21195v1 Announce Type: new Abstract: Discrete autoregressive (AR) text-to-image (T2I) models pair a VQ tokenizer with an AR policy, and current post-training pipelines optimize only the pol
arXiv:2605.21112v1 Announce Type: new Abstract: 4D automotive radar is indispensable for autonomous driving due to its low cost and robustness, yet its point cloud sparsity challenges 3D object detect
arXiv:2605.21127v1 Announce Type: new Abstract: Explicit reasoning models are trained to produce intermediate reasoning traces before final answers, but downstream fine-tuning is often performed on or
arXiv:2605.21300v1 Announce Type: new Abstract: Object hallucination is a significant challenge that hinders the application of large vision-language models (LVLMs) in practice. We hypothesize that on
arXiv:2605.20809v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable performance on zero-shot annotation tasks, they often struggle with the specialized convention
arXiv:2605.20654v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable capabilities, they remain susceptible to sophisticated, multi-step jailbreak attacks that circ
arXiv:2605.20277v1 Announce Type: new Abstract: Medical vision-language models (VLMs) have rapidly advanced as general-purpose multimodal assistants, yet their deployment in 3D Computed Tomography (CT
This article presents a maturity model for ML operations that leverages agent skills to improve on-call practices and incident response workflows. It likely discusses how organizations can evolve thei
arXiv:2605.21211v1 Announce Type: cross Abstract: In this work we present an efficient and practically implementable approach for the application of reinforcement learning (RL)-based control in chemic
arXiv:2605.21257v1 Announce Type: new Abstract: Planning through crowded environments under uncertain obstacle motions remains difficult, as stochastic interactions often induce overly conservative be
arXiv:2509.22963v3 Announce Type: replace Abstract: Reinforcement learning (RL) struggles to scale to large, combinatorial action spaces common in many real-world problems. This paper introduces a nov
arXiv:2605.20506v1 Announce Type: cross Abstract: Humans learn social norms and behaviors from verbal feedback (e.g., a parent saying 'that was rude' or a friend explaining 'here's why that hurt'). Ye
arXiv:2605.21256v1 Announce Type: new Abstract: Standard clinical Natural Language Processing (NLP) benchmarks often yield inflated metrics by forcing deterministic classification on ambiguous instanc
arXiv:2605.20823v1 Announce Type: new Abstract: Open-vocabulary 3D scene graph generation seeks to describe object instances and their relations with flexible natural-language predicates. The central
arXiv:2605.21440v1 Announce Type: new Abstract: Atmospheric turbulence severely degrades video quality by introducing distortions such as geometric warping, blur, and temporal flickering, posing signi
arXiv:2605.21237v1 Announce Type: new Abstract: Cardiac motion over a cardiac cycle is crucial for quantifying regional function and is strongly affected by cardiovascular diseases. Since temporally d
arXiv:2602.07832v2 Announce Type: replace Abstract: Process rewards have been widely used in deep reinforcement learning to improve training efficiency, reduce variance, and prevent reward hacking. In
Replit Enterprise is now available as a self-serve offering, allowing teams to quickly purchase the service, configure Single Sign-On (SSO) and SCIM provisioning, and begin collaborative development w
@Replit longer form video on Active Graph [7 min 22 sec] - flip the agent architecture - 1970s blackboard system - rollback, fork, diff agent runs - experience + behaviors + beliefs = you - behaviors
Replit shipped 5 new security tools in the last month: Security Agent, Auto-Protect, Security Center V2, External Access Tokens, and Private Publishing. 🛡️ Tomorrow we go live with @AlexandreCuoci, wh
arXiv:2605.20262v1 Announce Type: new Abstract: We study selective refusal editing as a three-way control problem: induce non-refusal on designated edit prompts while preserving benign behavior and ha
arXiv:2603.17784v2 Announce Type: replace Abstract: We developed a multi-label gastrointestinal video analysis pipeline based on a ResNet-50 frame classifier followed by anatomy-guided temporal event
arXiv:2605.20737v1 Announce Type: new Abstract: Existing approaches for unsupervised 3D point cloud segmentation predominantly rely on a purely visual similarity-based learning-by-clustering paradigm,
arXiv:2605.20708v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have become a de facto backbone of modern visual generation, and nearly every major axis of their design -- tokenization,
arXiv:2510.04905v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have significantly improved automated code generation. While existing approaches have achieved