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cs.IR2026
DoPR: Reusable Compressed Document Prefixes for Efficient LLM Reranking
Beiya Dai, Yifan Wei, Guang Yang +3
Large language models (LLMs) are effective rerankers, but pointwise reranking repeatedly processes the same document across different queries, causing substantial redundant documen…
cs.CL2026
Pretraining with Token-Level Adaptive Latent Chain-of-Thought
Boyi Zeng, Yiqin Hao, He Li +8
Scaling large language models by increasing parameters and training data is increasingly constrained by limited high-quality corpora and rising communication costs. This work explo…
cs.AI2026
Flow of Spans: Generalizing Language Models to Dynamic Span-Vocabulary via GFlowNets
Bo Xue, Yunchong Song, Fanghao Shao +5
Standard autoregressive language models generate text token-by-token from a fixed vocabulary, inducing a tree-structured state space when viewing token sampling as an action, which…