1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
PersonalAI 2.0: Enhancing knowledge graph traversal/retrieval with planning mechanism for Personalized LLM Agents
Mikhail Menschikov, Matvey Iskornev, Alexander Kharitonov +8
We introduce PersonalAI 2.0 (PAI-2), a novel framework designed to enhance LLM-based systems through integration of external knowledge graphs (KGs). The proposed approach addresses…
Contextual Linear Activation Steering of Language Models
Brandon Hsu, Daniel Beaglehole, Adityanarayanan Radhakrishnan +1
Linear activation steering is a powerful approach for eliciting the capabilities of large language models and specializing their behavior using limited labeled data. While effectiv…
Convergent Evolution: How Different Language Models Learn Similar Number Representations
Deqing Fu, Tianyi Zhou, Mikhail Belkin +2
Language models trained on natural text learn to represent numbers using periodic features with dominant periods at . In this paper, we identify a two-tiered hierarchy…
Catching rationalization in the act: detecting motivated reasoning before and after CoT via activation probing
Parsa Mirtaheri, Mikhail Belkin
Large language models (LLMs) can produce chains of thought (CoT) that do not accurately reflect the actual factors driving their answers. In multiple-choice settings with an inject…