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Long Phan

7 accepted papers

2025

Tamper-Resistant Safeguards for Open-Weight LLMs

ICLR 2025poster

Rapid advances in the capabilities of large language models (LLMs) have raised widespread concerns regarding their potential for malicious use. Open-weight LLMs present unique challenges, as existing safeguards lack robustness to tampering attacks that modify model weights. For example, recent works…

2025

Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs

NeurIPS 2025spotlight

As AIs rapidly advance and become more agentic, the risk they pose is governed not only by their capabilities but increasingly by their propensities, including goals and values. Tracking the emergence of goals and values has proven a longstanding problem, and despite much interest over the years it…

Cited by 0SourceScholar
2024

HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

ICML 2024poster

Automated red teaming holds substantial promise for uncovering and mitigating the risks associated with the malicious use of large language models (LLMs), yet the field lacks a standardized evaluation framework to rigorously assess new methods. To address this issue, we introduce HarmBench, a standa…

2024

Improving Alignment and Robustness with Circuit Breakers

NeurIPS 2024poster

AI systems can take harmful actions and are highly vulnerable to adversarial attacks. We present an approach, inspired by recent advances in representation engineering, that interrupts the models as they respond with harmful outputs with "circuit breakers." Existing techniques aimed at improving ali…

Cited by 65SourcePDFScholar
2024

Palmyra 3.0: A User-Friendly Cloud-Based Platform for Morphology and Dependency Syntax Annotation

COLING 2024main

We present Palmyra 3.0, a cloud-based, configurable, and user-friendly platform for morphology and syntax annotation through dependency-tree visualization. Palmyra 3.0 implements a robust system that stores data on the cloud. By default, Palmyra 3.0 comes with an Arabic dependency parser that genera…

2024

Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?

NeurIPS 2024poster

Performance on popular ML benchmarks is highly correlated with model scale, suggesting that most benchmarks tend to measure a similar underlying factor of general model capabilities. However, substantial research effort remains devoted to designing new benchmarks, many of which claim to measure nove…

Cited by 22SourcecodeScholar
2022

The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

NeurIPS 2022accept

As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop, a 1-year international and multidisciplinary initiative, was formed with the goal of researching and training large lan…

Cited by 214SourcePDFScholar