2026-03-23 15:16:59
Made new test prints on some off-cuts, using a slightly stronger developer solution than usual to see impact on max. depth. The main image (Eagle Creek, Oregon) is using 18% sodium acetate (curve corrected negative), the test strips are of 20% and 15% solutions (both uncorrected). The phone capture doesn't really show the differences too well, but I think I will go for the 18-20% from now on...
(Btw. The original image is here:
Quick test of recording from the mill on the $40 amazon USB microscope/endoscope/whatever camera.
Endmill is 250 μm diameter for scale, overall camera FOV a couple of mm. The QFN lands around the perimeter are 500 μm pitch.
Vibration degrades the image quite a bit when the motor is running due to the rather unstable mount I have right now. You can see in the last few seconds when I turn the spindle off, the image quality improves a lot.
Audio is not great, but with a mill s…
Just a little one and a half hour walk nearby before it was supposed to be raining (and rugby starts).
It was a nice walk and good to be out. Strangely, my old GPS device refused to get a location despite having lots of satellites. Just 10min before coming back (after a couple of restarts and taking the batteries out and back in) it worked.
Fortunately, I only had it with me to test if my heart rate monitor also connects to it.
Another AI depth mapping test, applying The vOICe for Android monocular AI depth view to the stereo vision test image <scene1.row3.col1.png> from the web page http://stereo--vision.com/kiji1e.html AI wrongly "thinks" the lamp is behind the bust, but otherwise it's not too bad.
Very few of us remember a company named Palantir.
No I don't mean that satanic data gathering atrocity that we read about in the daily news-of-the-awful.
No, I mean the company in the mid 1980's that built networked image scanners (sort of like a network of "office" ink jet printers.)
One of the cool aspects of their products is that they had a test program that would exercise the pieces of the machine - it would drive the various stepper motors and make i…
So, got the server in place but discovered that the Docker image that I created that has the Sisyphus client and all of the binaries like `ffmpeg`, `av1an` was not very happy. Ffmpeg crashed because it couldn't find the `libSvtAvcEnc.so.4` library which was because I had a custom version of it installed (`svt-av1-psyex`).
Got the Dockerfile fixed by installing `svt-av1-psyex` and then compiling `ffmpeg` against those libraries, then installing both `svt-av1-psyex` and `ffmpeg` int…
Series D, Episode 03 - Traitor
AVON: So Tarrant, this is your big moment.
TARRANT: If the teleport works.
VILA: It's working perfectly now, I checked it myself.
DAYNA: [Laughs] Yes, but would you use it yourself Vila? That's the real test.
https://blake.torpidity.net/m/403/176…
Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[5/5]:
- AppellateGen: A Benchmark for Appellate Legal Judgment Generation
Yang, Wang, Fan, Hu, Wang, Liu, Zeng, Fu, Gong, Zhang, Li, Zheng, Xu
https://arxiv.org/abs/2601.01331 https://mastoxiv.page/@arXiv_csCY_bot/115847038572575387
- Vision-Language Agents for Interactive Forest Change Analysis
James Brock, Ce Zhang, Nantheera Anantrasirichai
https://arxiv.org/abs/2601.04497 https://mastoxiv.page/@arXiv_csCV_bot/115864542639529766
- FigEx2: Visual-Conditioned Panel Detection and Captioning for Scientific Compound Figures
Jifeng Song, Arun Das, Pan Wang, Hui Ji, Kun Zhao, Yufei Huang
https://arxiv.org/abs/2601.08026 https://mastoxiv.page/@arXiv_csCV_bot/115892719657942341
- Sparse-RL: Breaking the Memory Wall in LLM Reinforcement Learning via Stable Sparse Rollouts
Luo, Zhang, Hu, Zhang, Wang, Su, Sun, Liang, Zhang
https://arxiv.org/abs/2601.10079 https://mastoxiv.page/@arXiv_csLG_bot/115904206341755873
- Compounding Disadvantage: Auditing Intersectional Bias in LLM-Generated Explanations Across India...
Amogh Gupta (Neil), Niharika Patil (Neil), Sourojit Ghosh (Neil), SnehalKumar (Neil), S Gaikwad
https://arxiv.org/abs/2601.14506 https://mastoxiv.page/@arXiv_csCY_bot/115937624654783353
- Measuring Complexity at the Requirements Stage: Spectral Metrics as Development Effort Predictors
Vierlboeck, Pugliese, Nilchian, Grogan, Babu
https://arxiv.org/abs/2602.07182 https://mastoxiv.page/@arXiv_csSE_bot/116045826365214235
- CoPE-VideoLM: Leveraging Codec Primitives For Efficient Video Language Modeling
Sarkar, Pautrat, Miksik, Pollefeys, Armeni, Rad, Dusmanu
https://arxiv.org/abs/2602.13191 https://mastoxiv.page/@arXiv_csCV_bot/116079824094529198
- MoD-DPO: Towards Mitigating Cross-modal Hallucinations in Omni LLMs using Modality Decoupled Pref...
Ashutosh Chaubey, Jiacheng Pang, Mohammad Soleymani
https://arxiv.org/abs/2603.03192 https://mastoxiv.page/@arXiv_csCV_bot/116170511143131333
- Image Generation Models: A Technical History
Rouzbeh Shirvani
https://arxiv.org/abs/2603.07455 https://mastoxiv.page/@arXiv_csCV_bot/116204960613280699
- Rethinking Attention Output Projection: Structured Hadamard Transforms for Efficient Transformers
Shubham Aggarwal, Lokendra Kumar
https://arxiv.org/abs/2603.08343 https://mastoxiv.page/@arXiv_csLG_bot/116205064359384079
- FGTR: Fine-Grained Multi-Table Retrieval via Hierarchical LLM Reasoning
Chaojie Sun, Bin Cao, Tiantian Li, Chenyu Hou, Ruizhe Li, Jing Fan
https://arxiv.org/abs/2603.12702 https://mastoxiv.page/@arXiv_csIR_bot/116237827836520478
- CausalEvolve: Towards Open-Ended Discovery with Causal Scratchpad
Yongqiang Chen, Chenxi Liu, Zhenhao Chen, Tongliang Liu, Bo Han, Kun Zhang
https://arxiv.org/abs/2603.14575 https://mastoxiv.page/@arXiv_csLG_bot/116243782215605653
- Silicon Bureaucracy and AI Test-Oriented Education: Contamination Sensitivity and Score Confidenc...
Yiliang Song, Hongjun An, Jiangan Chen, Xuanchen Yan, Huan Song, Jiawei Shao, Xuelong Li
https://arxiv.org/abs/2603.21636 https://mastoxiv.page/@arXiv_csAI_bot/116283590092117172
- Problems with Chinchilla Approach 2: Systematic Biases in IsoFLOP Parabola Fits
Eric Czech, Zhiwei Xu, Yael Elmatad, Yixin Wang, William Held
https://arxiv.org/abs/2603.22339 https://mastoxiv.page/@arXiv_csLG_bot/116288991182888131
- X-OPD: Cross-Modal On-Policy Distillation for Capability Alignment in Speech LLMs
Di Cao, Dongjie Fu, Hai Yu, Siqi Zheng, Xu Tan, Tao Jin
https://arxiv.org/abs/2603.24596 https://mastoxiv.page/@arXiv_eessAS_bot/116300009464853696
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