24 citations · 51 across the 27 of their papers we have counts for
5 papers · 2 filters
On-Policy Distillation Teaches New Skills but Not New Knowledge
Yixuan Tang, Yi Yang
On-policy distillation (OPD) strengthens language-model reasoning, yet whether students acquire new factual knowledge or compositional skill for multi-step reasoning remains unknow…
DREAM: Dense Retrieval Embeddings via Autoregressive Modeling
Yixuan Tang, Yi Yang
Dense retrieval embedding models are a fundamental component of modern retrieval-based AI systems. Most dense retrievers are trained with contrastive objectives, which require labe…
Crowded in B-Space: Calibrating Shared Directions for LoRA Merging
Yixuan Tang, Yi Yang
Merging separately trained LoRA adapters is a practical alternative to joint multi-task training, but it often hurts performance. Existing methods usually treat the LoRA update $ΔW…
Elastic Attention: Test-time Adaptive Sparsity Ratios for Efficient Transformers
Zecheng Tang, Quantong Qiu, Yi Yang +6
The quadratic complexity of standard attention mechanisms poses a significant scalability bottleneck for large language models (LLMs) in long-context scenarios. While hybrid attent…
KV-Embedding: Training-free Text Embedding via Internal KV Re-routing in Decoder-only LLMs
Yixuan Tang, Yi Yang
While LLMs are powerful embedding backbones, their application in training-free settings faces two structural challenges: causal attention restricts early tokens from accessing sub…