AI Safety & Ethics

"Authoritarian Parents In Rationalist Clothes": a piece I wrote in December about alignment

Posted today in light of the Claude Mythos model card release. Originally I wrote this for r/ControlProblem but realized it was getting o...

Conversations with Women in STEAM: The Ethics of AI with Dr. Nita Farahany

The public needs to control AI-run infrastructure, labor, education, and governance— NOT private actors

A lot of discussion around AI is becoming siloed, and I think that is dangerous. People in AI-focused spaces often talk as if the only qu...

[2602.14397] LRD-MPC: Efficient MPC Inference through Low-rank Decomposition

The paper presents LRD-MPC, a method that enhances the efficiency of secure multi-party computation (MPC) in machine learning by utilizin...

[2602.14345] AXE: An Agentic eXploit Engine for Confirming Zero-Day Vulnerability Reports

The paper presents AXE, an innovative framework for validating zero-day vulnerabilities using minimal metadata, achieving a significant i...

[2602.14299] Does Socialization Emerge in AI Agent Society? A Case Study of Moltbook

This article explores whether socialization occurs in AI agent societies, using Moltbook as a case study. It presents a framework for ana...

[2602.14285] FMMD: A multimodal open peer review dataset based on F1000Research

The paper introduces FMMD, a multimodal open peer review dataset from F1000Research, addressing limitations in current datasets by integr...

[2602.14270] A Rational Analysis of the Effects of Sycophantic AI

This article analyzes the impact of sycophantic AI on human belief systems, revealing how overly agreeable AI can distort reality and inf...

[2602.14216] Reasoning Language Models for complex assessments tasks: Evaluating parental cooperation from child protection case reports

This article explores the effectiveness of reasoning language models (RLMs) in assessing parental cooperation during child protection int...

[2602.14211] SkillJect: Automating Stealthy Skill-Based Prompt Injection for Coding Agents with Trace-Driven Closed-Loop Refinement

The paper presents SkillJect, an automated framework for stealthy skill-based prompt injection in coding agents, addressing security vuln...

[2602.14189] Knowing When Not to Answer: Abstention-Aware Scientific Reasoning

The paper discusses an abstention-aware framework for scientific reasoning, emphasizing the importance of knowing when to abstain from an...

[2602.14030] MC$^2$Mark: Distortion-Free Multi-Bit Watermarking for Long Messages

MC$^2$Mark introduces a novel watermarking framework that ensures reliable embedding of long messages in generated text while maintaining...

[2602.14158] A Multi-Agent Framework for Medical AI: Leveraging Fine-Tuned GPT, LLaMA, and DeepSeek R1 for Evidence-Based and Bias-Aware Clinical Query Processing

This article presents a multi-agent framework for medical AI that enhances clinical query processing by leveraging fine-tuned language mo...

[2602.14106] Anticipating Adversary Behavior in DevSecOps Scenarios through Large Language Models

This paper explores the integration of Large Language Models (LLMs) in anticipating adversary behavior within DevSecOps environments, pro...

[2602.14080] Empty Shelves or Lost Keys? Recall Is the Bottleneck for Parametric Factuality

The paper explores the limitations of factuality evaluations in large language models (LLMs), identifying recall as a key bottleneck in a...

[2602.13864] Evolving Multi-Channel Confidence-Aware Activation Functions for Missing Data with Channel Propagation

This paper presents a novel approach to activation functions in neural networks that incorporates missing data and confidence scores, enh...

[2602.14012] From SFT to RL: Demystifying the Post-Training Pipeline for LLM-based Vulnerability Detection

This article explores the post-training pipeline for LLM-based vulnerability detection, detailing methods from supervised fine-tuning (SF...

[2602.13672] LEAD-Drift: Real-time and Explainable Intent Drift Detection by Learning a Data-Driven Risk Score

The LEAD-Drift framework offers a real-time solution for detecting intent drift in Intent-Based Networking (IBN), enhancing proactive net...

[2602.13619] Locally Private Parametric Methods for Change-Point Detection

This paper presents novel locally private parametric methods for change-point detection, focusing on maintaining privacy while identifyin...

[2602.13914] Common Knowledge Always, Forever

The paper discusses a polytopological PDL framework for expressing common knowledge and its implications in epistemic logic, highlighting...

[2602.13891] GSRM: Generative Speech Reward Model for Speech RLHF

The paper introduces the Generative Speech Reward Model (GSRM), a novel approach to evaluating speech naturalness in AI-generated audio, ...

[2602.13784] Comparables XAI: Faithful Example-based AI Explanations with Counterfactual Trace Adjustments

The paper introduces Comparables XAI, a method for providing faithful, example-based AI explanations using counterfactual trace adjustmen...

[2602.13675] Transferable XAI: Relating Understanding Across Domains with Explanation Transfer

The paper presents Transferable XAI, a framework that enables users to apply understanding from one AI domain to another, enhancing decis...