Ronald Cardenas — accepted AI-conference papers

2026

A Benchmark for Deep Information Synthesis

Debjit Paul, Daniel Murphy, Milan Gritta, Ronald Cardenas, Victor Prokhorov, Lena Sophia Bolliger +11

ICLR 2026poster

Large language model (LLM)-based agents are increasingly used to solve complex tasks involving tool use, such as web browsing, code execution, and data analysis. However, current evaluation benchmarks do not adequately assess their ability to solve real-world tasks that require synthesizing informat…

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2025

SparsePO: Controlling Preference Alignment of LLMs via Sparse Token Masks

Fenia Christopoulou, Ronald Cardenas, Gerasimos Lampouras, Haitham Bou Ammar, Jun Wang

EMNLP 2025

Direct alignment algorithms have proven an effective step for aligning language models to human-desired behaviors. Current variants of the Direct Preference Optimization objective have focused on a strict setting where all tokens are contributing signals of KL divergence and rewards to the loss func

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2023

`Don't Get Too Technical with Me': A Discourse Structure-Based Framework for Automatic Science Journalism

Ronald Cardenas, Bingsheng Yao, Dakuo Wang, Yufang Hou

EMNLP 2023long main

Science journalism refers to the task of reporting technical findings of a scientific paper as a less technical news article to the general public audience. We aim to design an automated system to support this real-world task (i.e., automatic science journalism ) by 1) introducing a newly-constructe…

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