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Weizhi Zhang

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Preprint Aug 2026

XBridge: Entity-Grounded Latent Bridge for Heterogeneous LLM Communication

XBRIDGE is proposed, a decode-free communication protocol that outperforms text-based communication on all seven tasks for each model pair while achieving 11x lower latency, and in a same-architecture setting it also exceeds a KV-sharing baseline on six of seven tasks.

Wooseong Yang, Wei-Chieh Huang, Wei-Zhi Zhang et al. · 3 citations
#large language models Book Jul 2026

Personalized Recommendation Tool Learning via Autonomous Language Agents

An agent-based recommendation framework, memory-based Personalized Recommendation Tool learning via autonomous language Agents (PRTA), in which an LLM acts as a central planner interacting with multiple recommendation models as tools, demonstrating the superiority of PRTA over traditional recommendation and LLM-based b...

Ming-Dai Yang, Zhi-Wei Liu, Wei-Zhi Zhang et al. · 1 citation
#natural language process... Preprint Sep 2026

Random Attention: Rethinking KV Cache Eviction for Efficient Reasoning

Random Attention keeps the prompt and evicts uniformly at random within each attention head, computing no score at all; across four models and six reasoning tasks, it matches the strongest baseline in task performance while delivering 32-43% higher throughput than that method when deployed with vLLM.

Heng-Yi Wang, Jie-Lin Qiu, Wenting Zhao et al. · 0 citations
Jul 2026

BlockServe: Block-Grained Continuous Batching for High-Throughput Diffusion LLM Serving

BlockServe is presented, a continuous batching framework that integrates block-grained scheduling -- immediately evicting completed requests at block boundaries -- with mixed-state execution that extends dual cache and parallel decoding to heterogeneous batches via gather-scatter indexing.

Yuanjie Zhu, Liangwei Yang, Ke Xu et al. · 0 citations
Preprint Aug 2026

Harness the Memory: A Holistic Evaluation of Memory Substrates in Memory Agents

A controlled harness evaluation of memory substrates for memory-augmented agents, covering dense and sparse indices, text records, structural stores, hierarchical stores, refinement-based memories, parametric updates, and activation-compatible context mechanisms, shows that no single substrate consistently dominates.

Wei-Chieh Huang, Wei-Zhi Zhang, Yu-Chen Wu et al. · 2 citations

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