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cs.CL2026
Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models
Jia Deng, Junyi Li, Wayne Xin Zhao +3
Diffusion large language models (dLLMs) offer an efficient alternative to autoregressive models through parallel decoding, yet existing post-training methods largely rely on random…
cs.IR2026
Improving LLM-based Recommendation with Self-Hard Negatives from Intermediate Layers
Bingqian Li, Bowen Zheng, Xiaolei Wang +5
Large language models (LLMs) have shown great promise in recommender systems, where supervised fine-tuning (SFT) is commonly used for adaptation. Subsequent studies further introdu…