32 citations · 44 across the 12 of their papers we have counts for
9 papers · 1 filter
A BERTology View of LLM Orchestrations: Token- and Layer-Selective Probes for Efficient Single-Pass Classification
Gonzalo Ariel Meyoyan, Luciano Del Corro
Production LLM systems often rely on separate models for safety and other classification-heavy steps, increasing latency, VRAM footprint, and operational complexity. We instead reu…
Entropy Sentinel: Probing Entropy Traces for LLM Monitoring
Pedro Memoli Buffa, Luciano Del Corro
Deploying LLMs raises two coupled challenges: (1) monitoring---estimating where a model underperforms as traffic drifts---and (2) prioritization---deciding where to intervene to cl…
Are Optimal Algorithms Still Optimal? Rethinking Sorting in LLM-Based Pairwise Ranking with Batching and Caching
Juan Wisznia, Cecilia Bolaños, Juan Tollo +4
We introduce a novel framework for analyzing sorting algorithms in pairwise ranking prompting (PRP), re-centering the cost model around LLM inferences rather than traditional pairw…
The Greatest Good Benchmark: Measuring LLMs' Alignment with Utilitarian Moral Dilemmas
Giovanni Franco Gabriel Marraffini, Andrés Cotton, Noe Fabian Hsueh +3
The question of how to make decisions that maximise the well-being of all persons is very relevant to design language models that are beneficial to humanity and free from harm. We…
sPhinX: Sample Efficient Multilingual Instruction Fine-Tuning Through N-shot Guided Prompting
Sanchit Ahuja, Kumar Tanmay, Hardik Hansrajbhai Chauhan +9
Despite the remarkable success of large language models (LLMs) in English, a significant performance gap remains in non-English languages. To address this, we introduce a novel app…
Automatic Pair Construction for Contrastive Post-training
Canwen Xu, Corby Rosset, Ethan C. Chau +6
Alignment serves as an important step to steer large language models (LLMs) towards human preferences. In this paper, we propose an automatic way to construct contrastive data for…