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cs.LG2026
Failed Reasoning Traces Tell You What Is Fixable (But Not by Reading Them)
Nizar Islah, Istabrak Abbes, Irina Rish +2
When post-trained language models fail on reasoning problems, the common test-time-scaling response is to spend more compute on additional attempts, and the failed traces play no f…
cs.LG2025
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
Md Rifat Arefin, Gopeshh Subbaraj, Nicolas Gontier +4
Decoder-only Transformers often struggle with complex reasoning tasks, particularly arithmetic reasoning requiring multiple sequential operations. In this work, we identify represe…
cs.LG2024
Unsupervised Concept Discovery Mitigates Spurious Correlations
Md Rifat Arefin, Yan Zhang, Aristide Baratin +4
Models prone to spurious correlations in training data often produce brittle predictions and introduce unintended biases. Addressing this challenge typically involves methods relyi…