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    • 📌 2026 So Far — 11 Papers Accepted
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    • Online Conformal Abstention Under Adversarial Bandit Feedback
    • MJ: Multi-turn LLM Jailbreaking via Decomposed Credit Assignment
    • Transductive Generalization for GNNs via Optimal Transport
    • SAUL: Sharpness-Aware Augmented-Lagrangian Unlearning
    • The Interplay of Harness Design and Post-Training in LLM Agents
    • Can We Stop Malicious AI? KILLBENCH: A Benchmark for External AI Kill Switch Feasibility
    • The Illusion of Rust Safety: Detecting Modular Unsafe Functions with LLMs
    • Towards Functional Correctness of Large Code Models with Selective Generation
    • LLM Watermark Evasion via Bias Inversion
    • Ruby: Unmasking Unsafe Rust in Stripped Binaries via Machine Learning
    • Online Conformal Prediction with Adversarial Semi-bandit Feedback via Regret Minimization
    • ChronoBias: A Benchmark for Evaluating Time-conditional Group Bias in the Time-sensitive Knowledge of Large Language Models
    • Retrieval-Augmented Generation with Estimation of Source Reliability
    • Holistic Unlearning Benchmark: A Multi-Faceted Evaluation for Text-to-Image Diffusion Model Unlearning
    • ATLANTIS: AI-driven Threat Localization, Analysis, and Triage Intelligence System
    • SOUNDBOOST: Effective RCA and Attack Detection for UAV via Acoustic Side-Channel
    • Selective Generation for Controllable Language Models
    • TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction
    • MedBN: Robust Test Time Adaptation against Malicious Test Samples
    • PAC Prediction Sets Under Label Shift
    • Angelic Patches for Improving Third-Party Object Detector Performance
    • ACon$^2$: Adaptive Conformal Consensus for Provable Blockchain Oracles
    • CODiT: Conformal Out-of-Distribution Detection in Time-Series Data for Cyber-Physical Systems
    • PAC Prediction Sets for Meta-Learning
    • Sequential Covariate Shift Detection Using Classifier Two-Sample Tests
    • Towards PAC Multi-Object Detection and Tracking
    • PAC Prediction Sets Under Covariate Shift
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    • iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection
    • Calibrated prediction with covariate shift via unsupervised domain adaptation
    • PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction
    • Resilient linear classification: an approach to deal with attacks on training data
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The Illusion of Rust Safety: Detecting Modular Unsafe Functions with LLMs

Xiang Cheng
,
Fan Sang
,
Yibin Yang
,
Hang Zhang
,
Sangdon Park
,
Xiaokuan Zhang
,
Taesoo Kim
CCS , 2026
Last updated on May 16, 2026
← Can We Stop Malicious AI? KILLBENCH: A Benchmark for External AI Kill Switch Feasibility Aug 21, 2026
Towards Functional Correctness of Large Code Models with Selective Generation May 1, 2026 →