Papers with deep mechanistic analysis

1 papers
METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models (2026.acl-long)

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Challenge: Existing benchmarks evaluate contextual causal reasoning in fragmented settings, failing to ensure context consistency or cover the full causal hierarchy.
Approach: They use a unified context to benchmark large language models' contextual causal reasoning skills.
Outcome: The proposed benchmarks show that LLMs are susceptible to distraction by irrelevant but factually correct information at lower level of causality.

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