MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations
Large language model agents are increasingly evaluated as autonomous tool users, yet most benchmarks focus on bounded tasks with immediate success criteria. Real-world deployments often require Long-Term Coherence, the capacity to preserve purposeful behavior across extended horizons while adapting decisions to accumulated evidence. Evaluating this capacity requires a persistent environment in which actions constrain future choices, feedback arrives at heterogeneous delays, and incoherent behavi
Record details
Published: 30 July 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Agents & autonomy · Environment
Retrieved: 5 August 2026
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ethics.ai (30 July 2026), “MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations,” evidence record 16225, https://ethics.ai/record/16225 (originally published by HuggingFace Daily Papers).
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