2 citations · 4 across the 17 of their papers we have counts for
4 papers · 2 filters
Selecting What Matters: Semantic Compression-Guided Selective Pooling for Long-Context Embeddings
Zifeng Cheng, Jie Zheng, Zhiwei Jiang +4
Large language models (LLMs) have shown strong potential as training-free text encoders for long-context embeddings. Existing approaches primarily improve information flow under ca…
Focusing Condition: Inference-Time Self-Contrastive Steering Elicits Better Conditional Text Embeddings in LLMs
Zifeng Cheng, Lingyun Qian, Zhiwei Jiang +5
Extracting conditional text embeddings from large language models (LLMs) is a promising paradigm, as it requires neither additional data nor fine-tuning. Existing methods incorpora…
Accelerating Diffusion Language Models via Structured Suffix Modeling
Zifeng Cheng, Keda Li, Zhiwei Jiang +3
Diffusion Language Models (DLMs) exhibit strong parallel decoding capabilities by denoising multiple tokens in a single generation step. However, this parallelism comes with substa…
Step-Level On-Policy Distillation: Interpolating Between On-Policy Distillation and Supervised Fine-Tuning
Changhui Sun, Lanbo Liu, Hang Lei +11
On-policy distillation (OPD) aligns a student model with a teacher's logit distribution on student-generated trajectories. This approach has achieved strong empirical gains and can…