2026-10-31

A benchmark is not merely a collection of test questions; it naturally induces an empirical measure over difficulty. In this work, we develop this measure-based view of benchmark evaluation. This perspective allows us to identify and formalize two central failure modes: measure mismatch, where the benchmark difficulty distribution differs from the intended difficulty distribution, and coverage gaps, where uncovered regions along the difficulty axis prevent benchmarks from detecting meaningful lo

🤖This work formalizes benchmark evaluation through difficulty measures, identifies failure modes of measure mismatch and coverage gaps, and proposes diagnostic metrics and a rewriting algorithm to improve benchmark coverage.

Diffusion vision-language models (DVLMs) process their entire input at every denoising step. Since visual tokens make up 89-97% of this input on the benchmarks we study, most of the decoding computation is spent repeatedly processing the same image. Visual token pruning methods partially relieve this burden by removing part of the visual tokens, but they lose the removed information and still process the remaining image at every step. To measure how often the image is actually needed, we compare

🤖LOWN adaptively skips image processing during diffusion vision-language model decoding when predictions agree, reducing computation while preserving accuracy.

Generating videos of a specific subject from a few reference images remains challenging when the camera reveals surfaces that are not visible in the input. Early subject-to-video (S2V) methods condition on a single reference image and must therefore infer the subject's unseen appearance and geometry as the viewpoint changes. To address this limitation, recent methods extend S2V to multiple reference views, providing more information about the subject from different viewpoints. However, they do n

🤖OmniShowcase improves subject-to-video generation by using geometry-driven training data and surface-normal conditioning to maintain 3D consistency across novel viewpoints.

We present Youtu-Parsing-Omni, an omni-modal parser that converts documents, images, audio, and video into structured records grounded in space and time, providing a perception layer for agents that read, locate, and cite evidence across modalities. Its design rests on one encoder for every modality and one schema for every task. Youtu-Omni-Encoder, initialized from a pre-trained language model to strengthen text reading, encodes all modalities with shared weights in a unified space-time coordin

🤖Youtu-Parsing-Omni is a unified multi-modal parser that encodes documents, images, audio, and video into structured spatiotemporal records using shared weights and cross-modal fusion, achieving state-of-the-art results across parsing benchmarks through a self-evolving on-policy d

This week on Uncanny Valley, we also discuss Anthropic’s IPO filing and the volunteers gearing up to counter ICE at the midterms.

Akai teased its new MPC Sample Key on Instagram earlier this week, and said it plans to open-source its software so the modding community can hack it to their hearts' delight. While there's no word yet on when the device will launch or how much it will cost, The Verge has received exclusive images of […]

No Halloween costume? Just be a deceptively cute AI agent icon, a PHP vulnerability, or sleepy time Bryan Johnson.

EXCLUSIVE: A security researcher discovered the hardcoded credential in Applebee's app, allowing unrestricted access to customers' personal data.

dbreunig/nesformer Inspired by qwenputer by Divyansh Agrawal, Drew Breunig baked a working emulator for a Nintendo Entertainment System 6502 CPU into the weights of Qwen3.5-4B. You can now play NES ROMs such as Super Mario Bros (very slowly) running inside Qwen! In a comment on Hacker News Drew reveals the Opus 5.5 prompts he used to build this system: Read this article and any relevant source code: Then explore if you could emulate the chip and ram in a Nintendo Entertainment System (as people

A meteorite found in the Sahara is a rare piece of Mars' ancient crust.