activity
20172026
most citedLearning Deep Features for One-Class Classification

304 citations · 468 across the 20 of their papers we have counts for

collaborators

24 papers

cs.CL2026

PLSQLBench: Benchmarking LLM Systems for Executable Procedural Database Programming

Marianne Menglin Liu, Leonid Boytsov, Daniel W. Peterson +13

We present PLSQLBench, to our knowledge the first benchmark for evaluating whether LLMs can write executable PL/SQL programs, with correctness measured through execution-based test…

cs.CV2025

Descriminative-Generative Custom Tokens for Vision-Language Models

Pramuditha Perera, Matthew Trager, Luca Zancato +2

This paper explores the possibility of learning custom tokens for representing new concepts in Vision-Language Models (VLMs). Our aim is to learn tokens that can be effective for b…

cs.CL2024

Approximately Aligned Decoding

Daniel Melcer, Sujan Gonugondla, Pramuditha Perera +7

It is common to reject undesired outputs of Large Language Models (LLMs); however, current methods to do so require an excessive amount of computation to re-sample after a rejectio…

cs.LG2024

Compositional Structures in Neural Embedding and Interaction Decompositions

Matthew Trager, Alessandro Achille, Pramuditha Perera +2

We describe a basic correspondence between linear algebraic structures within vector embeddings in artificial neural networks and conditional independence constraints on the probab…

cs.CV2024

Multi-Modal Hallucination Control by Visual Information Grounding

Alessandro Favero, Luca Zancato, Matthew Trager +5

Generative Vision-Language Models (VLMs) are prone to generate plausible-sounding textual answers that, however, are not always grounded in the input image. We investigate this phe…

cs.CL2023★ 1 cited

Meaning Representations from Trajectories in Autoregressive Models

Tian Yu Liu, Matthew Trager, Alessandro Achille +3

We propose to extract meaning representations from autoregressive language models by considering the distribution of all possible trajectories extending an input text. This strateg…