To quantify this stagnation, we introduce LIVEVQA, the first-of-its-kind dataset featuring 107,143 samples and 12 categories data specifically designed to support research in both seeking and updating with live visual knowledge. Drawing from recent news articles, video platforms, and academic publications in April 2024-May 2025, LIVEVQA enables evaluation of how models handle latest visual information beyond their knowledge boundaries and how current methods help to update them. Our comprehensive benchmarking of 17 state-of-the-art MLLMs reveals significant performance gaps on content beyond knowledge cutoff, and tool-use or agentic visual seeking framework drastically gain an average of 327% improvement. Furthermore, we explore parameter-efficient fine-tuning (PEFT) methods to update MLLMs with new visual knowledge. We dive deeply to the critical balance between adapter capacity and model capability when updating MLLMs with new visual knowledge. All the experimental dataset and source code are publicly available at: https://livevqa.github.io.

Retrieval-Augmented Generation (RAG) empowers Large Language Models (LLMs) to dynamically integrate external knowledge during inference, improving their factual accuracy and adaptability. However, adversaries can inject poisoned external knowledge to override the model's internal memory. While existing attacks iteratively manipulate retrieval content or prompt structure of RAG, they largely ignore the model's internal representation dynamics and neuron-level sensitivities. The underlying mechanism of RAG poisoning has not been fully studied and the effect of knowledge conflict with strong parametric knowledge in RAG is not considered. In this work, we propose NeuroGenPoisoning, a novel attack framework that generates adversarial external knowledge in RAG guided by LLM internal neuron attribution and genetic optimization.

Training-free guidance enables controlled generation in diffusion and flow models, but most methods rely on gradients and assume differentiable objectives. This work focuses on training-free guidance addressing challenges from non-differentiable objectives and discrete data distributions. We propose TreeG: Tree Search-Based Path Steering Guidance, applicable to both continuous and discrete settings in diffusion and flow models. TreeG offers a unified framework for training-free guidance by proposing, evaluating, and selecting candidates at each step, enhanced with tree search over active paths and parallel exploration. We comprehensively investigate the design space of TreeG over the candidate proposal module and the evaluation function, instantiating TreeG into three novel algorithms. Our experiments show that TreeG consistently outperforms top guidance baselines in symbolic music generation, small molecule design, and enhancer DNA design with improvements of 29.01%,26.38%,and

Robust 3D geometry estimation from videos is critical for applications such as autonomous navigation, SLAM, and 3D scene reconstruction. Recent methods like DUSt3R demonstrate that regressing dense pointmaps from image pairs enables accurate and efficient pose-free reconstruction.

Large Language Models (LLMs) have demonstrated impressive performance across various tasks, yet they remain vulnerable to generating toxic content, necessitating detoxification strategies to ensure safe and responsible deployment. Test-time detoxification methods, which typically introduce static or dynamic interventions into LLM representations, offer a promising solution due to their flexibility and minimal invasiveness. However, current approaches often suffer from imprecise interventions, primarily due to their insufficient exploration of the transition space between toxic and non-toxic outputs. To address this challenge, we propose Autoregressive Reward Guided Representation Editing (ARGRE), a novel testtime detoxification framework that explicitly models toxicity transitions within the latent representation space, enabling stable and precise reward-guided editing. ARGRE identifies non-toxic semantic directions and interpolates between toxic and non-toxic representations to reveal fine-grained transition trajectories. These trajectories transform sparse toxicity annotations into dense training signals, enabling the construction of an autoregressive reward model that delivers stable and precise editing guidance. At inference, the reward model guides an adaptive two-step editing process to obtain detoxified representations: it first performs directional steering based on expected reward gaps to shift representations toward non-toxic regions, followed by lightweight gradient-based refinements. Extensive experiments across 8 widely used LLMs show that ARGRE significantly outperforms leading baselines in effectiveness (-62.21%

LLM-based agents have demonstrated great potential in generating and managing code within complex codebases. In this paper, we introduce WebGen-Bench, a novel benchmark designed to measure an LLM-based agent's ability to create multifile website codebases from scratch. It contains diverse instructions for website generation, created through the combined efforts of human annotators and GPT4o. These instructions span three major categories and thirteen minor categories, encompassing nearly all important types of web applications. To assess the quality of the generated websites, we generate test cases targeting each functionality described in the instructions. These test cases are then manually filtered, refined, and organized to ensure accuracy, resulting in a total of 647 test cases. Each test case specifies an operation to be performed on the website and the expected outcome of the operation. To automate testing and improve reproducibility, we employ a powerful web-navigation agent to execute test cases on the generated websites and determine whether the observed responses align with the expected results. We evaluate three high-performance code-agent frameworks--Bolt.diy,

Trump turns on the charm after extended'alpha' handshake with Macron and kisses for Brigitte at Palace of Versailles Sensational REAL reason Jelly Roll is divorcing Bunnie XO: Insiders reveal'preacher's wife' bombshell that's the talk of Nashville... truth about legendary rocker cuckolding rumor... and G-string mishap LIZ JONES: The cracks in Harry and Meghan's perfect facade have started to show. It's so obvious he's tiring of her tone-deaf approach... and I predict there's serious trouble in store Taylor Swift's bottomless thirst for attention, her greed and sheer tackiness are now truly unbearable... this latest stunt has shown her true colors: MAUREEN CALLAHAN NBA star's fiancee breaks her silence after friend, 26, mysteriously dropped dead at her luxury bachelorette party in St Barts Luxury fashion tycoon beloved by the stars hangs her head in shame as she's indicted for allegedly exploiting her workers and stealing $50k from their wages Jeff Bezos mercilessly mocked for taking'fake phone calls' when out with wife Lauren Sanchez Anguished family members flee court over sick details of Gilgo Beach murderer's kill room: Live updates'She has not been transparent... the damage has been done': How influencer Elle Darby'betrayed' thousands of young female fans...as insiders tell MOLLY CLAYTON how she cashed in As a divorced mother-of-three, cocaine was my little treat while my fellow middle-class friends had a few wines. What happened next was every family's worst nightmare... this is my warning to mums who'dabble' Desperate search for mom-of-three who hasn't been seen in three days as husband pleads for her return The shocking betrayal behind Jelly Roll's divorce from Bunnie XO is so utterly cruel... but have you yet spotted her revenge: JACQUELYNN POWERS Devastating supply crunch forces Apple to raise prices on iPhones and other devices, calling the move'unavoidable' Jeff's Dream Team: Bezos recruits world's top architects to build most expensive mega mansion on Billionaire Bunker island The Ring star Daveigh Chase's friends searched for her on LA's Skid Row in months before her shock death at 35 Watch horrifying drone video that follows woman's plunge to death after bungee team threw her from bridge without rope Renowned scientist Neil deGrasse Tyson tells US government to'Show the alien!' after latest UFO disclosure Astrophysicist Neil deGrasse Tyson wants the US government to'Show the alien!' after the latest UFO disclosure from the Trump administration . Tyson, 67, joined The Fox News Rundown on Monday, explaining how the overwhelming amount of irrefutable evidence should finally be topped off with a picture of an extraterrestrial being. 'Is it too much to ask at this point for them to just show the alien?

Target speaker extraction focuses on isolating a specific speaker's voice from an audio mixture containing multiple speakers. To provide information about the target speaker's identity, prior works have utilized clean audio samples as conditioning inputs. However, such clean audio examples are not always readily available. For instance, obtaining a clean recording of a stranger's voice at a cocktail party without leaving the noisy environment is generally infeasible. Limited prior research has explored extracting the target speaker's characteristics from noisy enrollments, which may contain overlapping speech from interfering speakers. In this work, we explore a novel enrollment strategy that encodes target speaker information from the noisy enrollment by comparing segments where the target speaker is talking (Positive Enrollments) with segments where the target speaker is silent (Negative Enrollments). Experiments show the effectiveness of our model architecture, which achieves over 2.1 dB higher SI-SNRi compared to prior works in extracting the monaural speech from the mixture of two speakers. Additionally, the proposed two-stage training strategy accelerates convergence, reducing the number of optimization steps required to reach 3 dBSNR by 60%. Overall, our method achieves state-of-the-art performance in the monaural target speaker extraction conditioned on noisy enrollments.

This paper presents a unified framework that allows high-quality dynamic Gaussian Splatting from both defocused and motion-blurred monocular videos. Due to the significant difference between the formation processes of defocus blur and motion blur, existing methods are tailored for either one of them, lacking the ability to simultaneously deal with both of them. Although the two can be jointly modeled as blur kernel-based convolution, the inherent difficulty in estimating accurate blur kernels greatly limits the progress in this direction. In this work, we go a step further towards this direction. Particularly, we propose to estimate per-pixel reliable blur kernels using a blur prediction network that exploits blur-related scene and camera information and is subject to a blur-aware sparsity constraint. Besides, we introduce a dynamic Gaussian densification strategy to mitigate the lack of Gaussians for incomplete regions, and boost the performance of novel view synthesis by incorporating unseen view information to constrain scene optimization. Extensive experiments show that our method outperforms the state-of-the-art methods in generating photorealistic novel view synthesis from defocused and motion-blurred monocular videos.

Trump turns on the charm after extended'alpha' handshake with Macron and kisses for Brigitte at Palace of Versailles Sensational REAL reason Jelly Roll is divorcing Bunnie XO: Insiders reveal'preacher's wife' bombshell that's the talk of Nashville... truth about legendary rocker cuckolding rumor... and G-string mishap LIZ JONES: The cracks in Harry and Meghan's perfect facade have started to show. It's so obvious he's tiring of her tone-deaf approach... and I predict there's serious trouble in store Taylor Swift's bottomless thirst for attention, her greed and sheer tackiness are now truly unbearable... this latest stunt has shown her true colors: MAUREEN CALLAHAN NBA star's fiancee breaks her silence after friend, 26, mysteriously dropped dead at her luxury bachelorette party in St Barts Luxury fashion tycoon beloved by the stars hangs her head in shame as she's indicted for allegedly exploiting her workers and stealing $50k from their wages Jeff Bezos mercilessly mocked for taking'fake phone calls' when out with wife Lauren Sanchez Anguished family members flee court over sick details of Gilgo Beach murderer's kill room: Live updates'She has not been transparent... the damage has been done': How influencer Elle Darby'betrayed' thousands of young female fans...as insiders tell MOLLY CLAYTON how she cashed in As a divorced mother-of-three, cocaine was my little treat while my fellow middle-class friends had a few wines. What happened next was every family's worst nightmare... this is my warning to mums who'dabble' Desperate search for mom-of-three who hasn't been seen in three days as husband pleads for her return The shocking betrayal behind Jelly Roll's divorce from Bunnie XO is so utterly cruel... but have you yet spotted her revenge: JACQUELYNN POWERS Devastating supply crunch forces Apple to raise prices on iPhones and other devices, calling the move'unavoidable' Jeff's Dream Team: Bezos recruits world's top architects to build most expensive mega mansion on Billionaire Bunker island The Ring star Daveigh Chase's friends searched for her on LA's Skid Row in months before her shock death at 35 Watch horrifying drone video that follows woman's plunge to death after bungee team threw her from bridge without rope Stonehenge's secret SISTER: Archaeologists discover an ancient monument just three miles away that may have served as a'prototype' for the famous stones Archaeologists have discovered a secret sister monument to Stonehenge that might have served as a'prototype' for the famous stones. This ancient site is just three miles away from Stonehenge itself, located in the village of Bulford, Wiltshire. Consisting of two wooden poles placed 400 feet (120 metres) apart, this long-lost monument might appear rather basic at first glance.