Papers by Ryan Saklad

1 papers
Can Large Language Models Infer Causal Relationships from Real-World Text? (2026.acl-long)

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Challenge: Existing work evaluating large language models relies on synthetic or simplified texts with explicit causal relationships.
Approach: They develop a benchmark to evaluate LLMs' ability to infer causal relationships from texts . they use a dataset of texts with different levels of explicitness and complexity .
Outcome: The proposed benchmark is the first-ever real-world dataset for this task.

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