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Does Dynamic-Point Filtering Help When Texture Is Scarce? A Controlled Study of ORB-SLAM2 Front-Ends in Synthetic Indoor Scenes
arXiv:2610.10564v1 Announce Type: new Abstract: Dynamic-point filters are routinely added to feature-based visual SLAM, and several recent systems argue that removing dynamic features can leave too few static features in low-texture regions. So far, these systems have been evaluated only on texture-rich benchmark sequences. We present a controlled study that isolates this interaction. We render synthetic indoor sequences in which surface texture (four levels, quantified by FAST-corner density and image-gradient entropy) and scene dynamics (three levels) are varied factorially along identical camera trajectories, with stereo, RGB-D, ground-truth poses and dynamic masks. On this grid we compare ORB-SLAM2 without filtering, with an optical-flow and epipolar-residual filter (FLOW), and with a multi-view depth-consistency filter (GEOM), and report trajectory error, tracking completeness and surviving static features over five runs. Because the masks give per-keypoint ground truth, we also m
Teaching a Robot Dog New Tricks: Diverse Quadruped Skills via Combined Reinforcement and Imitation Learning with Adversarial Task Selection
arXiv:2610.10601v1 Announce Type: new Abstract: Reinforcement Learning (RL) has enabled legged robots to perform a range of skills in single-task settings. However, applications such as farm robotics or space exploration require diverse skills such as locomotion, digging, or close-range surveying. Training an end-to-end policy to address this problem remains difficult due to challenges such as sample inefficiency and gradient conflict between tasks in multi-task learning. We propose a three-stage method that trains a single policy to perform distinct tasks such as walking, digging, and hopping, and compose them into novel behaviors such as crawling. First, multiple teacher policies are trained using RL on narrowly defined tasks. Then, two additional stages train a student policy with a multi-teacher distillation setup that uses a combined RL and Imitation Learning (IL) objective under an adversarial task selection process that focuses training on the worst-performing task. With this me
Freeze the Decoder, Heal the Encoder: Parameter-Efficient Adaptation for SVD-Based KV-Cache Compression
arXiv:2610.10552v1 Announce Type: new Abstract: Comparing parameter-efficient fine-tuning recipes under a single, shared learning rate is a common but flawed practice: when the arms being compared have very different trainable-parameter counts, a shared rate can simultaneously depress the larger arms' means and inflate their variance, manufacturing a large, seemingly multi-seed-significant advantage for the smallest arm that is not a real effect. We document this confound in a concrete setting: post-hoc SVD-based KV-cache compression, where an already-pretrained model is converted to a low-rank (multi-head-latent-attention-style) cache by factorizing its key/value weights into a down-projection ("encoder") and an up-projection ("decoder"), after which a short fine-tune ("healing") recovers the accuracy lost to truncation. Under a shared learning rate, freezing the decoder and healing only the encoder looks like a clear win over healing the decoder or both factors; once every arm is giv
From Claude Code to Codex: The Harness Is the Product
Continue reading on JIN System Architect »
A Step-by-Step Guide for Developing Your Personal Agentic System Using Ollama
Build a private, local AI assistant that can plan tasks, use tools, remember context, and automate your everyday work without relying on Continue reading on Medium »
How to Build an AI Investigation Workflow That Doesn’t Hallucinate
I know it can be tough to trust AI with your company s most critical data.Continue reading on Medium »
If Claude Is So Good, Why Doesn’t Anthropic’s CEO Use It to Write?
In January 2026, Dario Amodei published The Adolescence of Technology, a roughly 20,000-word essay on the risks of powerful AI.Continue reading on Medium »
Are Em Dashes a Sign of AI Writing? What the 2026 Evidence Says
The ChatGPT dash became the internet s favorite AI tell. The data from 2026 tells a very different story.Continue reading on ILLUMINATION »
The Growth of AI Crime Markets and the Challenge for Banking Security
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OpenAI, the Partition Principle, and Mathematics
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President Trump awards Big Tech donors with nation’s highest science prizes
Together, the awardees have donated nearly $6 billion to efforts tied to Trump and his administration.
US plans livestream of execution by firing squad
The United States' execution of the Fort Hood shooter will be livestreamed, anonymous officials from the Defense Department told the BBC and Associated Press. The planned execution of Nidal Hasan, the former US Army major convicted of killing 13 people at the Texas military base, was announced this week. He is scheduled to be executed by firing squad on December 3rd at 2PM ET. The Verge contacted YouTube, Twitch, TikTok, Meta, Rumble, and Kick to ask if they plan to allow the livestream to be aired on their platforms. None responded before publication. "We'll make sure that people are able to watch it, that it's public, because people need … Read the full story at The Verge.