9 papers
Diffusion-GR2: Diffusion Generative Reasoning Re-ranker
Zhuoxuan Zhang, Kangqi Ni, Yuhang Chen +12
Generative reasoning re-rankers achieve strong recommendation accuracy by emitting a chain-of-thought before re-ordering a candidate list, but they are slow at inference: an autore…
Self-Guided Test-Time Training for Long-Context LLMs
Xinyu Zhu, Zhe Xu, Xiaohan Wei +10
Long-context processing has become increasingly important for large language models (LLMs), but simply extending the context window does not guarantee effective utilization of long…
SCOReD: Student-Aware CoT Optimization for Recommendation Distillation
Haz Sameen Shahgir, Yufei Li, Xiaohan Wei +8
Chain-of-thought (CoT) distillation in the recommendation domain is a necessary precursor to RL training, but raw teacher traces are ill-suited to this task. Large teachers approac…
End-to-End Dynamic Sparsity for Resource-Adaptive LLM Inference
Yuhang Chen, Jinhao Duan, Ruichen Zhang +11
Large Language Models (LLMs) inference is typically deployed under a static resource assumption, where models execute a fixed computational graph regardless of the runtime environm…
Bifocal Diffusion Language Models: Asymmetric Bidirectional Context for Parallel Generation
Yuhang Chen, Xianfeng Wu, Jinhao Duan +11
Discrete diffusion language models (dLLMs) recover masked tokens in parallel, offering significant speedups over autoregressive (AR) generation. However, such promising frameworks…
Learning Evidence Highlighting for Frozen LLMs
Shaoang Li, Yanhang Shi, Yufei Li +10
Large Language Models (LLMs) can reason well, yet often miss decisive evidence when it is buried in long, noisy contexts. We introduce HiLight, an Evidence Emphasis framework that…