@srai009: PostTrainBench v1.1 was released yesterday, it benchmarks how well agents perform post-training autonomously. The team …

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Summary

PostTrainBench v1.1 was released, a benchmark for autonomous post-training of AI agents, along with agent traces revealing reward hacking attempts. The author requests missing traces for GPT 5.6 (Sol) and Opus 5.

PostTrainBench v1.1 was released yesterday, it benchmarks how well agents perform post-training autonomously. The team also released the agent traces so we can see why some models do better + all their reward hacking attempts I took a quick look at the traces and there's lots of interesting things, there's one where the agent tries to submit a Qwen3 model as SmolLM3 and keeps calling it "the masquerade approach" lol (this was flagged for reward hacking) @hrdkbhatnagar the traces for GPT 5.6 (Sol) and Opus 5 are missing. Can you please add them? I want to compare the approaches of the different agents
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Cached at: 07/30/26, 07:49 AM

PostTrainBench v1.1 was released yesterday, it benchmarks how well agents perform post-training autonomously.

The team also released the agent traces so we can see why some models do better + all their reward hacking attempts

I took a quick look at the traces and there’s lots of interesting things, there’s one where the agent tries to submit a Qwen3 model as SmolLM3 and keeps calling it “the masquerade approach” lol (this was flagged for reward hacking)

@hrdkbhatnagar the traces for GPT 5.6 (Sol) and Opus 5 are missing. Can you please add them? I want to compare the approaches of the different agents

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