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cs.CL2026
LoopCD: Loop-wise Contrastive Decoding for Improving Reasoning in Looped Language Models
Byeongho Yu, Junhyuk So, Eunhyeok Park
Looped Language Models (LoopLMs) perform "latent reasoning" by recursively refining internal latent representations with shared weights, offering a more effective alternative to ex…
cs.CL2025
PruneCD: Contrasting Pruned Self Model to Improve Decoding Factuality
Byeongho Yu, Changhun Lee, Jungyu Jin +1
To mitigate the hallucination problem in large language models, DoLa exploits early exit logits from the same model as a contrastive prior. However, we found that these early exit…