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Author

D. Ranasinghe

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Jul 2026

Representation Trajectories Matters: Complementary Evidence for OOD Detection and Image Classification

This work asks whether the resulting computation path contains evidence that the final representation discards, and whether that evidence improves OOD detection and image classification on clean and shifted data, and whether that evidence improves OOD detection and image classification on clean and shifted data.

I. M. De La Jara, Cristian Rodriguez-Opazo, Hamed Damirchi et al. · 0 citations
#artificial intelligence Preprint Sep 2026

SAFEGuard: Detect Optimization-Based Jailbreak Attacks Through Harmful Semantic Analysis and Fluency Measurement

This work proposes a unified detection framework SAFEGuard which incorporates a hybrid fluency measurement based on cross-layer distribution distance and perplexity, and the analysis of harmful semantics through gradient matching, and demonstrates the effectiveness of SAFEGuard against evolving jailbreak attacks.

Quoc le Viet Vo, Trung Le, D. Ranasinghe et al. · 0 citations
Preprint Aug 2026

Reasoning Errors Have a Region and a Direction in the Residual-Stream Trajectory of LLMs

It is suggested that reasoning validity is better read from state-conditioned motion than from either static states or decontextualized trajectories alone, andlations show that motion, region, and direction provide complementary signals.

Hamed Damirchi, I. M. De La Jara, D. Ranasinghe et al. · 0 citations
Preprint Aug 2026

InSPECtor: Improving SLEIGH Processor Specification Veracity via Proxy

This study is a significant undertaking to enable, for the first time, the systematic validation of open-source SLEIGH language specifications, predominantly used by Ghidra, with a testing framework based on an automated oracle validation strategy by proxy.

Michael Chesser, Paul Quirk, D. Cooke et al. · 0 citations
Jul 2026

Level, Sharpness, and Corpus: Why Zero-Shot OOD Detector Rankings Do Not Transfer

The Complementary Evidence Guard (CEG), a detector-agnostic wrapper that preserves complementary evidence through a non-compensatory fusion of the base detector, level, and sharpness using only empirical in-distribution percentiles is introduced.

I. M. De La Jara, Cristian Rodriguez-Opazo, Stephen Gould et al. · 0 citations

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