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cs.LG2026
Towards Self-Explainable Document Visual Question Answering with Chain-of-Explanation Predictions
Kjetil Indrehus, Adrian Duric, Changkyu Choi +1
Document Visual Question Answering (DocVQA) requires vision-language models to reason not only about what information in a document is relevant to a question, but also where the an…
cs.CL2026
Beyond Accuracy: Decomposing the Reasoning Efficiency of LLMs
Daniel Kaiser, Arnoldo Frigessi, Ali Ramezani-Kebrya +1
As reasoning LLMs increasingly trade tokens for accuracy through deliberation, search, and self-correction, a single accuracy score can no longer tell whether those tokens buy usef…