activity
20232026
most citedOverPrompt: Enhancing ChatGPT through Efficient In-Context Learning

4 citations · 18 across the 33 of their papers we have counts for

collaborators
Showing 2026 · cs.CLShow all

5 papers · 2 filters

cs.CL2026

Self-Distillation with Verbal Regularization

Jiazheng Li, Yawei Li, Junru Lu +7

On-policy self-distillation (OPSD) trains a large language model using supervision from a teacher instantiated from the same model as the student. The teacher is conditioned on pri…

cs.CL2026

Follow the Latent Roadmap: Navigating Revocable Decoding for Diffusion LLMs with Anchor Tokens

Yizhen Yao, Qinglin Zhu, Runcong Zhao +4

Diffusion Large Language Models (dLLMs) offer a promising avenue for parallel generation but face a trade-off between decoding speed and quality. While revocable decoding strategie…

cs.CL2026

Detecting Contextual Hallucinations in LLMs with Frequency-Aware Attention

Siya Qi, Yudong Chen, Runcong Zhao +6

Hallucination detection is critical for ensuring the reliability of large language models (LLMs) in context-based generation. Prior work has explored intrinsic signals available du…

cs.CL2026

Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding

Yanzheng Xiang, Lan Wei, Yizhen Yao +8

Parallel diffusion decoding can accelerate diffusion language model inference by unmasking multiple tokens per step, but aggressive parallelism often harms quality. Revocable decod…

cs.CL2026

Beyond RAG for Agent Memory: Retrieval by Decoupling and Aggregation

Zhanghao Hu, Qinglin Zhu, Runcong Zhao +4

Standard Retrieval Augmented Generation (RAG) is poorly matched to agent memory. Unlike large heterogeneous corpora, agent memory forms a bounded and coherent interaction stream in…