HANDBOOK.md introduces a benchmark specifically designed to evaluate long-context agentic instruction following in language-model agents. This benchmark assesses how well agents adhere to a system prompt, policy file, or skills document during their operations.
arxiv.org
2 min
9h ago
HANDBOOK.md introduces a benchmark specifically designed to evaluate long-context agentic instruction following in language-model agents. This benchmark assesses how well agents adhere to a system prompt, policy file, or skills document during their operations.
arxiv.org
2 min
9h ago
HANDBOOK.md introduces a benchmark specifically designed to evaluate long-context agentic instruction following in language-model agents. This benchmark assesses how well agents adhere to a system prompt, policy file, or skills document during their operations.
arxiv.org
2 min
9h ago
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