4 papers
SHERLOC: Structured Diagnostic Localization for Code Repair Agents
Hovhannes Tamoyan, Sean Narenthiran, Erik Arakelyan +2
LLM agents solve repository-level coding tasks through multi-turn tool use, but utilize half their budget on locating faults before editing. Dedicated localization frameworks have…
More Yap Less Meaning: Uncovering Self-Improvement Behavior in SLMs
Marina Igitkhanian, Erik Arakelyan
Recently, language models have made rapid progress across various domains and applications. However, their capability for self-improvement, i.e., whether they are adept at recognis…
FLARE: Faithful Logic-Aided Reasoning and Exploration
Erik Arakelyan, Pasquale Minervini, Pat Verga +2
Modern Question Answering (QA) and Reasoning approaches based on Large Language Models (LLMs) commonly use prompting techniques, such as Chain-of-Thought (CoT), assuming the result…
With Great Backbones Comes Great Adversarial Transferability
Erik Arakelyan, Karen Hambardzumyan, Davit Papikyan +4
Advances in self-supervised learning (SSL) for machine vision have improved representation robustness and model performance, giving rise to pre-trained backbones like \emph{ResNet}…