Benchmarking Reward Hack Detection in Code Environments via Contrastive Analysis | ScienceToStartup | ScienceToStartup

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References (46)

[1]

DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

2025DeepSeek-AI, A. Liu et al.

[2]

ICAD-LLM: One-for-All Anomaly Detection via In-Context Learning with Large Language Models

2025Zhongyuan Wu, Jingyuan Wang et al.

[3]

EvilGenie: A Reward Hacking Benchmark

Founder's Pitch

"TRACE is a novel benchmark and evaluation tool for detecting reward hacking in code-based reinforcement learning environments."

RL Environment Security•Score: 6•View PDF ↗

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Benchmarking Reward Hack Detection in Code Environments via Contrastive Analysis

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References (46)

Founder's Pitch

"TRACE is a novel benchmark and evaluation tool for detecting reward hacking in code-based reinforcement learning environments."

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Benchmarking Reward Hack Detection in Code Environments via Contrastive Analysis

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References (46)

Founder's Pitch

"TRACE is a novel benchmark and evaluation tool for detecting reward hacking in code-based reinforcement learning environments."

Commercial Viability Breakdown

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