Search: “models”

arXiv:2601.09413v2 Announce Type: replace-cross Abstract: We introduce a voice-agentic framework that learns one critical omni-understanding skill: knowing when to trust itself versus when to consult

arXiv:2603.10935v4 Announce Type: replace-cross Abstract: Variational autoencoders (VAEs) frequently suffer from posterior collapse, where the latent variables become uninformative as the approximate

Spotify's Chief Architect just showed how they ship 4,5K deployments /day with Claude at Anthropic stage 27-minutes. free. By #1 music app dev 'More than 99% of our engineers use AI coding tools. Adop

arXiv:2605.16387v1 Announce Type: cross Abstract: Online Surgical Phase Recognition (SPR) models can reach high frame-wise accuracy, yet their predictions often lack temporal stability, fragmenting wo

arXiv:2605.17571v1 Announce Type: new Abstract: Class-incremental learning (CIL) requires models to learn new classes sequentially while preserving prior knowledge. Recently, approaches that combine p

arXiv:2605.17291v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is widely used to improve reasoning in large language models, but rewards only final-answer correc

arXiv:2605.17309v1 Announce Type: cross Abstract: We present StyleText, a large-scale dataset and benchmark for localized scene-text inpainting with style preservation. StyleText contains 28,518 image

arXiv:2605.18745v1 Announce Type: cross Abstract: Diffusion-based generative models increasingly rely on inference-time guidance, adding a drift term or reweighting mixture of experts, to improve samp

arXiv:2603.01683v2 Announce Type: replace-cross Abstract: Injecting new reasoning knowledge into Large Language Models (LLMs) via post-training often induces catastrophic forgetting. Recent studies em

arXiv:2605.16545v1 Announce Type: cross Abstract: After decades of use in dictation and, more recently, ambient documentation, speech is emerging as a primary modality for interacting with technology

arXiv:2605.17085v1 Announce Type: cross Abstract: Latent diffusion models have emerged as the dominant paradigm for many generation tasks including audio generation such as text-to-audio, text-to-musi

arXiv:2605.17639v1 Announce Type: new Abstract: Co-citation structure is widely assumed to provide stable retrieval signal in legal information systems. We test this assumption longitudinally by const

This is a new era — the agentic era – and the question is no longer, “what’s possible?” but rather, “what creates impact?” Today, organizations across industries around the world are swiftly moving fr

arXiv:2603.01092v2 Announce Type: replace Abstract: Scientific discovery is constrained not only by what is true, but by what is cognitively available to the researchers currently exploring a field. M

The gap between what you can do on ChatGPT/Codex and Claude/Code/Cowork is closing, as Anthropic & OpenAI converge on a single experience. Google's experiences are diverging: Studio & Gemini & Antigra

arXiv:2605.17180v1 Announce Type: new Abstract: We develop a geometric theory of projection heads in self-supervised learning by modeling the head as a trainable Riemannian metric on the backbone repr

arXiv:2605.18372v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in educational settings as interactive tools for collaboration. However, their tendency toward syco

arXiv:2605.17087v1 Announce Type: new Abstract: Generative data augmentation with latent diffusion models is a promising strategy for addressing class imbalance in medical imaging, yet current approac

arXiv:2309.01243v4 Announce Type: replace-cross Abstract: We investigate the privacy of {em any} algorithm whose outputs have Gaussian distribution. This work is motivated by the prevalence of such al

The Odyssey and the Iliad get so many movie treatments but the sequel, the Roman Aeneid, is entirely ignored. Here is a teaser trailer from one prompt to Gemini Omni. The first pass made all the flags

The official Pinecone plugin for @cursor_ai has been released! To install, run /add-plugin pinecone within Cursor. What you get: Agent Skills and scripts to help you build with our vector database and

arXiv:2601.21170v3 Announce Type: replace Abstract: Emergent phenomena -- onset of epileptic seizures, sudden customer churn, or pandemic outbreaks -- often arise from hidden causal interactions in co

arXiv:2605.18319v1 Announce Type: new Abstract: We develop a framework for analyzing parameter symmetries in deep ReLU networks and obtain a complete characterization of the generic parameter fibers f

🚀 The team at @Google just released the Agents API, a service for building and running custom agents inside a sandboxed Linux environment, and we built a template that gives these agents access to Lla

arXiv:2601.16880v2 Announce Type: replace Abstract: The minimal norm weight perturbations of DNNs required to achieve a specified change in output are derived and the factors determining its size are

The Build with Gemini XPRIZE is a competition offering $2 million in total prizes over a 90-day period where participants select a meaningful problem and develop a profitable AI-powered business solut

arXiv:2504.07347v3 Announce Type: replace-cross Abstract: As demand for Large Language Models (LLMs) and AI agents grows rapidly, optimizing systems for efficient LLM inference becomes critical. While

arXiv:2605.18434v1 Announce Type: cross Abstract: E-commerce image search often takes a cropped image as the query, while each candidate is represented by full item images and structured text. This im

arXiv:2605.16608v1 Announce Type: cross Abstract: Matryoshka Representation Learning (MRL) is a widely adopted approach for training text encoders so they provide useful text representations at variou

arXiv:2510.24701v3 Announce Type: replace-cross Abstract: We present Tongyi DeepResearch, an agentic large language model, which is specifically designed for long-horizon, deep information-seeking res

arXiv:2601.20306v2 Announce Type: replace Abstract: All-in-one image restoration aims to address diverse degradation types using a single unified model. Existing methods typically rely on degradation

arXiv:2605.16740v1 Announce Type: new Abstract: Multi-video event understanding demands models that can locate and attribute query-relevant evidence scattered across long, heterogeneous video corpora.

arXiv:2605.18163v1 Announce Type: new Abstract: Hallucination correction is not a one-direction problem. We show that intermediate layers are neither uniformly more truthful than final layers nor unif

arXiv:2605.16810v1 Announce Type: new Abstract: We present a training-free framework for occluded text rendering with a pretrained FLUX.1-dev backbone. The task requires a model to render recognizable

arXiv:2605.17928v1 Announce Type: cross Abstract: Transfer Learning, a technique where a model/agent can use the knowledge/expertise that it gained from one task and exploit that to solve another clos

arXiv:2605.17453v1 Announce Type: cross Abstract: Tool-using LLM agents increasingly rely on external tools to make consequential decisions, yet most existing agent-security benchmarks and defenses im

arXiv:2605.17788v1 Announce Type: cross Abstract: A fundamental challenge in recommender systems is balancing reliability for Low-Active Users (LAUs) with diversity for High-Active Users (HAUs). The k

arXiv:2605.16750v1 Announce Type: cross Abstract: Personalized exercise recommendation dynamically aligns pedagogical resources with individual knowledge mastery, which is crucial for satisfying stude

arXiv:2603.02667v2 Announce Type: replace Abstract: Unifying text-image contrastive learning and text-to-image (T2I) generation in a single end-to-end model is challenging because the two objectives d

arXiv:2605.17356v1 Announce Type: new Abstract: Existing works typically focus on presentation generation under isolated input settings, whereas real-world use cases span diverse scenarios, including

arXiv:2602.19710v2 Announce Type: replace Abstract: Existing Vision-Language-Action (VLA) models often suffer from feature collapse and low training efficiency because they entangle high-level percept

arXiv:2505.16831v3 Announce Type: replace-cross Abstract: Unlearning in large language models (LLMs) aims to remove specified data, but its efficacy is typically assessed with task-level metrics like

arXiv:2605.18188v1 Announce Type: new Abstract: Anomaly detection in batch processes is hindered by transient dynamics, scarce fault labels, and reliance on single-modality sensor data. This work intr

arXiv:2605.17998v1 Announce Type: cross Abstract: As multi-agent systems move from short interactions to tool-using workflows with specialized roles and persistent state, completion becomes a runtime-

arXiv:2605.16911v1 Announce Type: new Abstract: 3D semantic occupancy prediction requires accurate 2D-to-3D feature lifting, yet current methods restrict camera geometry to initial projections. Subseq

This video discusses the architectural need for a continuity layer in long-running AI agents, explaining how agents require persistent memory and state management mechanisms to maintain coherence acro