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Justin Wang

7 accepted papers

2026

EVMbench: Evaluating AI Agents on Smart Contract Security

ICML 2026poster

Smart contracts on public blockchains now manage large amounts of value, and vulnerabilities in these systems can lead to substantial losses. As AI agents become more capable at reading, writing, and running code, it is natural to ask how well they can already navigate this landscape, both in ways t…

Cited by 0SourceScholar
2025

AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents

ICLR 2025poster

The robustness of LLMs to jailbreak attacks, where users design prompts to circumvent safety measures and misuse model capabilities, has been studied primarily for LLMs acting as simple chatbots. Meanwhile, LLM agents---which use external tools and can execute multi-stage tasks---may pose a greater…

Cited by 36SourcePDFScholar
2025

Building A Proof-Oriented Programmer That Is 64% Better Than GPT-4o Under Data Scarcity

ACL 2025finding

Existing LMs struggle with proof-oriented programming due to data scarcity, which manifest in two key ways: (1) a lack of sufficient corpora for proof-oriented programming languages such as F*, and (2) the absence of large-scale, project-level proof-oriented implementations that can teach the model…

2025

Diversification Catalyzes Language Models’ Instruction Generalization To Unseen Semantics

ACL 2025finding

Instruction-tuned language models excel in knowledge, reasoning, and instruction-following. While knowledge and reasoning are well-explored, the factors enabling generalization to unseen instructions remain underexplored due to challenges in isolating instruction-following dynamics.In this work, we…

2025

ShorterBetter: Guiding Reasoning Models to Find Optimal Inference Length for Efficient Reasoning

NeurIPS 2025poster

Recent models such as OpenAI o1 and DeepSeek-R1 have demonstrated strong performance on reasoning-intensive tasks by generating extended Chain-of-Thought (CoT) traces. While longer reasoning helps with thorough exploration of solution paths for complex problems, it also often leads to inefficient an…

Cited by 0SourceScholar
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…

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