Publications by Zeming Chen | EPFL Graph Search

Search for high-mass exclusive diphoton production with tagged protons in proton-proton collisions at √s=13 TeV

Matthias Finger, Qian Wang, Varun Sharma, Konstantin Androsov, Jan Steggemann, Ian Smith, Xin Chen, Rakesh Chawla, Michele De Palma, Matteo Galli

A search is presented for high-mass exclusive diphoton production via photon-photon fusion in proton-proton collisions at root s = 13 TeV in events where both protons survive the interaction. The analysis utilizes data corresponding to an integrated lumino ...

AMER PHYSICAL SOC2024

Discovering Knowledge-Critical Subnetworks in Pretrained Language Models

Antoine Bosselut, Zeming Chen, Negar Foroutan Eghlidi, Deniz Bayazit

Pretrained language models (LMs) encode implicit representations of knowledge in their parameters. However, localizing these representations and disentangling them from each other remains an open problem. In this work, we investigate whether pretrained lan ...

Association for Computational Linguistics2024

Monotonicity Reasoning in the Age of Neural Foundation Models

Zeming Chen, Qiyue Gao

The recent advance of large language models (LLMs) demonstrates that these large-scale foundation models achieve remarkable capabilities across a wide range of language tasks and domains. The success of the statistical learning approach challenges our unde ...

Springer2023

Mitigating Label Biases for In-context Learning

Antoine Bosselut, Zeming Chen

Various design settings for in-context learning (ICL), such as the choice and order of the in-context examples, can bias the model's predictions. While many studies discuss these design choices, there have been few systematic investigations into categorizi ...

Assoc Computational Linguistics-Acl2023

DISCO: Distilling Counterfactuals with Large Language Models

Antoine Bosselut, Zeming Chen, Qiyue Gao

Models trained with counterfactually augmented data learn representations of the causal structure of tasks, enabling robust generalization. However, high-quality counterfactual data is scarce for most tasks and not easily generated at scale. When crowdsour ...

Assoc Computational Linguistics-Acl2023