most citedExternal Evaluation of Discrimination Mitigation Efforts in Meta's Ad Delivery

2 citations · 2 across the 8 of their papers we have counts for

collaborators

9 papers

cs.LG2026

Memory-Computation Tradeoffs in Semi Amortized Parametric Optimization

Shijie Pan, Agustin Castellano, Zeyu Shen +1

Learning-enabled decision systems often use offline data or computation to reduce online compute cost. Despite the empirical success of such approaches, there is limited general un…

cs.AI2026

Using Cognitive Models to Improve Language Model Simulation of Human Persuasion Games

Zirui Cheng, Zeyu Shen, Thomas L. Griffiths +1

People make decisions differently in strategic interactions. Some update beliefs like a Bayesian; others exhibit biases like motivated reasoning. Although creators of large languag…

cs.LG2026

Temporally Extended Mixture-of-Experts Models

Zeyu Shen, Peter Henderson

Mixture-of-Experts models, now popular for scaling capacity at fixed inference speed, switch experts at nearly every token. Once a model outgrows available GPU memory, this churn c…

cs.LG2026

The Geometry of Alignment Collapse: When Fine-Tuning Breaks Safety

Max Springer, Chung Peng Lee, Blossom Metevier +5

Fine-tuning aligned language models on benign tasks unpredictably degrades safety guardrails, even when training data contains no harmful content and developers have no adversarial…

cs.LG2025

FrontierCS: Evolving Challenges for Evolving Intelligence

Qiuyang Mang, Wenhao Chai, Zhifei Li +48

We introduce FrontierCS, a benchmark of 156 open-ended problems across diverse areas of computer science, designed and reviewed by experts, including CS PhDs and top-tier competiti…

cs.SE2025

AutoCode: LLMs as Problem Setters for Competitive Programming

Shang Zhou, Zihan Zheng, Kaiyuan Liu +18

Writing competitive programming problems is exacting. Authors must: set constraints, input distributions, and edge cases that rule out shortcuts; target specific algorithms (e.g.,…

cs.CR2025

ReliabilityRAG: Effective and Provably Robust Defense for RAG-based Web-Search

Zeyu Shen, Basileal Imana, Tong Wu +3

Retrieval-Augmented Generation (RAG) enhances Large Language Models by grounding their outputs in external documents. These systems, however, remain vulnerable to attacks on the re…

cs.CY2025★ 2 cited

External Evaluation of Discrimination Mitigation Efforts in Meta's Ad Delivery

Basileal Imana, Zeyu Shen, John Heidemann +1

The 2022 settlement between Meta and the U.S. Department of Justice to resolve allegations of discriminatory advertising resulted is a first-of-its-kind change to Meta's ad deliver…

cs.SE2025

LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?

Zihan Zheng, Zerui Cheng, Zeyu Shen +16

Recent reports claim that large language models (LLMs) now outperform elite humans in competitive programming. Drawing on knowledge from a group of medalists in international algor…