Kimi K2.7-Code cuts thinking tokens 30% — but practitioners say the benchmarks don't check out

Kimi K2.7-Code claims 30% fewer thinking tokens and a drop-in API swap path, but independent benchmarks show kernel regressions and no DeepSWE submission.
Tech Times

Open-Source Coding Model Ornith-1.0 Writes Its Own Training Scaffold in Reinforcement Learning

Open-source agentic coding model Ornith-1.0, released today under the MIT license, uses a self-improving reinforcement ...
XDA Developers on MSN

I used Meta Llama 4, Qwen 3-Coder and Gemma 4 to develop a Python app, and only one model is worth keeping for developers

Putting some of the best local models to the development test ...
GitHub

Are CLIP features all you need for Universal Synthetic Image Origin Attribution?

Trust What You learN (TWYN) Workshop of ECCV 2024. Abstract: The steady improvement of Diffusion Models for visual synthesis has given rise to many new and interesting use cases of synthetic images ...
GitHub

You Don't Need Strong Assumptions: Temporal Difference Visual Representation Learning

TDV is a self-supervised video representation learning method built on a single causal assumption: the past causes the future. A frame encoder and motion encoder are trained jointly such that the ...