N3Xxus_6
Joined 5 years ago
Karma
53
Submissions
52
Member since
Oct 9
Recent submissions
Comment · 3 months ago
I'm the co-creator of agentre-bench, an agentic benchmark that measures how well models can reverse engineer malware. Currently it measures only ELF malware but PE will be included in the next update. We also just released a Qwen 3.59b model, https://huggingface.co/AgentreBench/xref-9b This model went through SFT, then reinforcement learning, specifically IPO. Our research has recently been mentioned by several universities as well.
Comment · 8 months ago
My team and I have worked on an agentic benchmark to see how well agents can perform at reverse engineering threats. The results are pretty interesting, we would love the communities feedback.
Comment · 9 months ago
Over the last year I’ve been building RacoGrad, a deep learning library written in Racket (a Lisp). It started as an experiment in understanding autodiff and neural nets from first principles, but it’s grown into something surprisingly usable.
Recently, with help of opencalw I added transformer support and finished a working GPT-2 implementation. The model loads pretrained GPT-2 weights and runs end to end inference entirely in Racket.
Comment · 1 year ago
Large language models (LLMs) demonstrate impressive capabilities across numerous domains, from programming and technical support to cooking instructions and research enhancement. However, they continue to struggle with precise symbol manipulation in tasks requiring rigorous logical reasoning, mathematical proofs, and complex algebraic operations. As a student of philosophy and computer science, I find this intersection especially fascinating because of the connections between logical precision and conceptual clarity.