Category
3,920 papers
Experiments on multiple LVLMs show that the Balanced Fitting method consistently outperforms prior PTQ approaches under both weight-only and weight-activation quantization, while lower reconstruction loss does not reliably translate into better downstream performance.
CMES (Cross-Modal Emotion Stimuli), a multi-source collection of emotion-conditioned stories, real facial expressions, synthetic portraits, and synthetic emotion-evoking scenes, suggests that emotion representations can share relational structure and causal effects across sources, modalities, and architectures, even wh...
It is demonstrated that high natural-trajectory accuracy can coexist with weak controlled target-state responsiveness in fixed representation-readout pairs and adding responsiveness and context sensitivity to a failure predictor reduces policy-failure prediction error on new initializations relative to the specified ba...
ReaLVR is proposed, which brings visual-evidence supervision to the model's own free-running latent trajectories, and is the first to scale visual reasoning in latent space, showing that the framework continues to deliver robust improvements at frontier model scales up to 235B.
Reach audiences
Advertise in front of researchers, engineers, and readers.
World models for manipulation are typically trained from video, yet the events that determine how manipulation unfolds, such as making and releasing contact, are difficult to observe visually and are often easier to sense through touch. We present the Dexterous Tactile World Model (DTWM), a video world model for future...
This paper proposes a 3D point tracker accurate in those absolute terms and operating within a single commodity GPU, pose-free, monocular budget, exceeding strong feed-forward trackers and a companion analysis explains why several published trackers lose most of their accuracy under this budget.
In diffusion-based generation, a neural network can be trained to predict the clean data, the noise, or the velocity from a noisy input, yet plain Diffusion Transformers operating on large pixel patches succeed with clean prediction and fail with noise or velocity prediction.
Across four forecasting tasks spanning object motion, vegetation greenness and solar power, ViBR-WM achieves lower mean overall physical-target error than Temporal Straightening, ConvLSTM, PredRNN and SimVP on every task.
This paper introduces a posterior sampling algorithm customized for the pyramidal/cascaded architecture, which relies on a coarse to fine hierarchical strategy to generate images in the pixel domain and presents CLIMB-Flow which alternates between three steps: an end-point estimation from the current coarse and noisy i...
This work proposes O-Attack, a highly transferable black-box attack framework that outperforms six state-of-the-art methods in black-box transferability, with consistent effectiveness across prompts and improved efficiency and imperceptibility.
Constrained Edit Fields (CEF) achieves state-of-the-art Structure Distance, background LPIPS, and background MSE with both Stable Diffusion 3.5 Medium and FLUX, while retaining competitive instruction alignment.
PARA is proposed, which retains the frozen prompt prediction as a support-invariant semantic anchor and incorporates a visual prediction learned from the support set through an anchor-relative residual and achieves state-of-the-art performance in both few-shot classification and base-to-novel generalization.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
A Blog post by H company on Hugging Face
A Blog post by Liquid AI on Hugging Face
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
