5 papers
Cross-Model In-Context Neurofeedback Reveals (Limited) Activation Control in LLMs
Davide Baldelli, Robyn Kozierok, Mirko Bronzi +1
Probes on activation vectors are widely used to detect misbehavior in language models, but their success relies on the assumption that models cannot control what their activations…
Probabilistic Calibration Is a Trainable Capability in Language Models
Davide Baldelli, Sruthi Kuriakose, Maryam Hashemzadeh +2
Language models are increasingly used in settings where outputs should follow an intended distribution, yet their generation probabilities are often poorly calibrated to it. In man…
LLMs Can't Play Hangman: On the Necessity of a Private Working Memory for Language Agents
Davide Baldelli, Ali Parviz, Amal Zouaq +1
As LLMs move from text completion toward autonomous agents, they remain constrained by the standard chat interface, which lacks private working memory. This raises a fundamental qu…
CADmium: Fine-Tuning Code Language Models for Text-Driven Sequential CAD Design
Prashant Govindarajan, Davide Baldelli, Jay Pathak +2
Computer-aided design (CAD) is the digital construction of 2D and 3D objects, and is central to a wide range of engineering and manufacturing applications like automobile and aviat…
TWOLAR: a TWO-step LLM-Augmented distillation method for passage Reranking
Davide Baldelli, Junfeng Jiang, Akiko Aizawa +1
In this paper, we present TWOLAR: a two-stage pipeline for passage reranking based on the distillation of knowledge from Large Language Models (LLM). TWOLAR introduces a new scorin…