activity
20202026
most citedFactual Consistency of Multilingual Pretrained Language Models

16 citations · 31 across the 14 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CL2024

Defining Knowledge: Bridging Epistemology and Large Language Models

Constanza Fierro, Ruchira Dhar, Filippos Stamatiou +2

Knowledge claims are abundant in the literature on large language models (LLMs); but can we say that GPT-4 truly "knows" the Earth is round? To address this question, we review sta…

cs.CL2024★ 2 cited

How Do Multilingual Language Models Remember Facts?

Constanza Fierro, Negar Foroutan, Desmond Elliott +1

Large Language Models (LLMs) store and retrieve vast amounts of factual knowledge acquired during pre-training. Prior research has localized and identified mechanisms behind knowle…

cs.CL2024

MuLan: A Study of Fact Mutability in Language Models

Constanza Fierro, Nicolas Garneau, Emanuele Bugliarello +2

Facts are subject to contingencies and can be true or false in different circumstances. One such contingency is time, wherein some facts mutate over a given period, e.g., the presi…

cs.CL2024

Does Instruction Tuning Make LLMs More Consistent?

Constanza Fierro, Jiaang Li, Anders Søgaard

The purpose of instruction tuning is enabling zero-shot performance, but instruction tuning has also been shown to improve chain-of-thought reasoning and value alignment (Si et al.…

cs.CL2024★ 1 cited

Learning to Plan and Generate Text with Citations

Constanza Fierro, Reinald Kim Amplayo, Fantine Huot +4

The increasing demand for the deployment of LLMs in information-seeking scenarios has spurred efforts in creating verifiable systems, which generate responses to queries along with…