8 citations · 14 across the 9 of their papers we have counts for
9 papers
Incentive-Aware Multi-Fidelity Optimization for Generative Advertising in Large Language Models
Jiayuan Liu, Barry Wang, Jiarui Gan +4
Generative advertising in large language model (LLM) responses requires optimizing sponsorship configurations under two strict constraints: the strategic behavior of advertisers an…
Command-V: Pasting LLM Behaviors via Activation Profiles
Barry Wang, Avi Schwarzschild, Alexander Robey +4
Retrofitting large language models (LLMs) with new behaviors typically requires full finetuning or distillation-costly steps that must be repeated for every architecture. In this w…
LLMs unlock new paths to monetizing exploits
Nicholas Carlini, Milad Nasr, Edoardo Debenedetti +5
We argue that Large language models (LLMs) will soon alter the economics of cyberattacks. Instead of attacking the most commonly used software and monetizing exploits by targeting…
NoveltyBench: Evaluating Language Models for Humanlike Diversity
Yiming Zhang, Harshita Diddee, Susan Holm +5
Language models have demonstrated remarkable capabilities on standard benchmarks, yet they struggle increasingly from mode collapse, the inability to generate diverse and novel out…
Are Triggers Needed for Document-Level Event Extraction?
Shaden Shaar, Wayne Chen, Maitreyi Chatterjee +3
Most existing work on event extraction has focused on sentence-level texts and presumes the identification of a trigger-span -- a word or phrase in the input that evokes the occurr…
IQA-EVAL: Automatic Evaluation of Human-Model Interactive Question Answering
Ruosen Li, Ruochen Li, Barry Wang +1
To evaluate Large Language Models (LLMs) for question answering (QA), traditional methods typically focus on assessing single-turn responses to given questions. However, this appro…
Private Hierarchical Governance for Encrypted Messaging
Armin Namavari, Barry Wang, Sanketh Menda +5
The increasing harms caused by hate, harassment, and other forms of abuse online have motivated major platforms to explore hierarchical governance. The idea is to allow communities…
Probing Representations for Document-level Event Extraction
Barry Wang, Xinya Du, Claire Cardie
The probing classifiers framework has been employed for interpreting deep neural network models for a variety of natural language processing (NLP) applications. Studies, however, h…
Automatic Error Analysis for Document-level Information Extraction
Aliva Das, Xinya Du, Barry Wang +4
Document-level information extraction (IE) tasks have recently begun to be revisited in earnest using the end-to-end neural network techniques that have been successful on their se…