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Up to 31.6% of correct model solutions rely on semantically invalid reasoning traces that look deceptively sound, revealing that chain-of-thought generation frequently acts as an unfaithful facade rather than a true computation graph.
LLMs struggle with instruction following in Indic languages despite progress in high-resource languages, as shown by a new benchmark spanning 14 languages.