activity
20192026
most citedExploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction

6 citations · 10 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Welcome to the Age of Agent Ads: Using On-Policy Attacks to Steer Agentic Decisions

Tim R. Davidson, Marija Šakota, Joshua Joseph +1

People increasingly delegate option-ranking tasks (e.g., shopping, job search, travel) to AI agents, which creates incentives to steer agentic decisions via "agent ads." To defend…

cs.CL2026

Integrating Machine-Generated Short Descriptions into the Wikipedia Android App: A Pilot Deployment of Descartes

Marija Šakota, Dmitry Brant, Cooltey Feng +7

Short descriptions are a key part of the Wikipedia user experience, but their coverage remains uneven across languages and topics. In previous work, we introduced Descartes, a mult…

cs.CL2025

Combining Constrained and Unconstrained Decoding via Boosting: BoostCD and Its Application to Information Extraction

Marija Šakota, Robert West

Many recent approaches to structured NLP tasks use an autoregressive language model to map unstructured input text to output text representing structured objects (such…

cs.CL2024

Edisum: Summarizing and Explaining Wikipedia Edits at Scale

Marija Šakota, Isaac Johnson, Guosheng Feng +1

An edit summary is a succinct comment written by a Wikipedia editor explaining the nature of, and reasons for, an edit to a Wikipedia page. Edit summaries are crucial for maintaini…

cs.CL2023★ 6 cited

Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction

Martin Josifoski, Marija Sakota, Maxime Peyrard +1

Large language models (LLMs) have great potential for synthetic data generation. This work shows that useful data can be synthetically generated even for tasks that cannot be solve…

cs.CL2022★ 2 cited

Descartes: Generating Short Descriptions of Wikipedia Articles

Marija Sakota, Maxime Peyrard, Robert West

Wikipedia is one of the richest knowledge sources on the Web today. In order to facilitate navigating, searching, and maintaining its content, Wikipedia's guidelines state that all…

cs.MA2019★ 2 cited

Putting Ridesharing to the Test: Efficient and Scalable Solutions and the Power of Dynamic Vehicle Relocation

Panayiotis Danassis, Marija Sakota, Aris Filos-Ratsikas +1

We study the optimization of large-scale, real-time ridesharing systems and propose a modular design methodology, Component Algorithms for Ridesharing (CAR). We evaluate a diverse…