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20242026
most citedNEZHA: A Zero-sacrifice and Hyperspeed Decoding Architecture for Generative Recommendations

1 citations · 1 across the 13 of their papers we have counts for

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cs.CL2026

TRACE: State-Aware Query Processing over Temporal Evidence Graphs for Conversational Data

Maolin Wang, Yu Wang, Zichun Liu +5

Conversational data is increasingly used as a persistent source of user state for long-running assistants and AI agents. However, querying this data remains challenging because con…

cs.CL2026

SEARCH-R: Structured Entity-Aware Retrieval with Chain-of-Reasoning Navigator for Multi-hop Question Answering

Yuqing Fu, Yimin Deng, Wanyu Wang +9

Multi-hop Question Answering (MHQA) aims to answer questions that require multi-step reasoning. It presents two key challenges: generating correct reasoning paths in response to th…

cs.CL2026

Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression

Jingyu Peng, Maolin Wang, Nan Wang +7

Despite substantial advancements in aligning large language models (LLMs) with human values, current safety mechanisms remain susceptible to jailbreak attacks. We hypothesize that…

cs.CL2026

Job Skill Extraction via LLM-Centric Multi-Module Framework

Guojing Li, Zichuan Fu, Junyi Li +8

Span-level skill extraction from job advertisements underpins candidate-job matching and labor-market analytics, yet generative large language models (LLMs) often yield malformed s…

cs.CL2026

AdaSwitch: Balancing Exploration and Guidance in Knowledge Distillation via Adaptive Switching

Jingyu Peng, Maolin Wang, Hengyi Cai +5

Small language models (SLMs) are crucial for applications with strict latency and computational constraints, yet achieving high performance remains challenging. Knowledge distillat…

cs.CL2026

Align-GRAG: Anchor and Rationale Guided Dual Alignment for Graph Retrieval-Augmented Generation

Derong Xu, Pengyue Jia, Xiaopeng Li +9

Despite the strong abilities, large language models (LLMs) still suffer from hallucinations and reliance on outdated knowledge, raising concerns in knowledge-intensive tasks. Graph…