8 papers
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…
Active Learners as Efficient PRP Rerankers
JeremÃas Figueiredo Paschmann, Juan Kaplan, Francisco Nattero +3
Pairwise Ranking Prompting (PRP) elicits pairwise preference judgments from an LLM, which are then aggregated into a ranking, usually via classical sorting algorithms. However, jud…
Autonomous Knowledge Graph Exploration with Adaptive Breadth-Depth Retrieval
JoaquÃn Polonuer, Lucas Vittor, Iñaki Arango +4
Retrieving evidence for language model queries from knowledge graphs requires balancing broad search across the graph with multi-hop traversal to follow relational links. Similarit…
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…
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…
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…