we propose a Hybrid Auditing Protocol: delegate deterministically verifiable logic to code; reserve LLMs for complex semantic evaluation.
This has direct implications for GenAI governance and also for Agentic AI systems that rely on reasoning traces to plan and make decisions
Excited to share that our paper “The Stability Trap: Evaluating the Reliability of LLM-Based Instruction Adherence Auditing” has been accepted at ACM Fairness, Accountability & Transparency (FAccT) conference 2026 🎉
Paper: https://t.co/sIf5Szqjv4
📐 We introduce the SID Framework to classify instructions into Objective (Syntactic & Semantic) and Subjective types — isolating the specific drivers of judge instability.
And the response is you need a PIR/claim reference number?? I explained that I discovered water damage after I got back home. Check the damage here and there’s more - this is upsetting. @flyethiopian please create a claim for me and process this case
@flyethiopian I flew Ethiopian from Bombay to SFO 4 weeks ago. On arrival my bags were damp but I didn’t think much of it. At home I realized the contents of my bag (food plus new clothes) were damaged. I reported this in an email and it took 4 weeks for y’all to reply
I’m not a puppet Elon.. I’m a daughter of two immigrant parents that had to work their ass off to provide for me! I’m a product of welfare, I’m a product of section 8, I’m a product of poverty and I’m a product of what happens when the system is set up against you….But you don’t know nothing about that. You don’t know not one thing about the American struggle…. PS fix my algorithm
@CasualBrady Thank you for a beautifully structured course on causal inference which is also free to access. Your ability to explain extremely difficult concepts with ease is inspiring and very appreciated. Thanks!
Excited about #LLM solutions? We are too! So, let’s understand the #LLMOps challenges in pre & post-production. Using our #Fiddler#chatbot as an LLM app example, I’ll be discussing the tips & tricks at #AIForward 2023! Register now: https://t.co/e8VhjHUS24
#MLOps#DataScience
The fact that most individual neurons are uninterpretable presents a serious roadblock to a mechanistic understanding of language models. We demonstrate a method for decomposing groups of neurons into interpretable features with the potential to move past that roadblock.