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Yongbin Liu

ACL 2026×2NeurIPS 2026推理长上下文与架构评测与基准对齐与偏好效率与系统
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0 一作 · 3 篇 · ACL 2026 / NeurIPS 2026

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2026 顶会论文

3
作者位次 #11/14ACL 2026Poster· Natural Language Processing

C omp T ab: A Comprehensive Benchmark for Real-World T able QA with Complex Reasoning and Irregular Tables

Zhen Yang · Wei Du · Jie Wang · Wenze Zhou · Xiangfeng Meng · Zhengyang Wang · Suping Sun · Ziwei Du · Haodong Zou · Jie Chen · Yongbin Liu · Shicheng Tan · jiahao ying · Shu Zhao

摘要

Recent progress in Large Language Model (LLM) based Table Question Answering (TableQA) has demonstrated strong performance on standard benchmarks. However, existing benchmarks mainly focus on well-structured tables and fail to reflect the irregular structures and complex reasoning commonly encoun...

评测与基准推理对齐与偏好OpenReview 项目页
作者位次 #2/4ACL 2026Findings· Findings of ACL

R an L o RA : Residual-aware Nonlinear Low-Rank Adaptation

Xu Luo · Yongbin Liu · Chunping Ouyang · Ying Yu

摘要

Low-Rank Adaptation (LoRA) is a widely adopted approach for parameter-efficient fine-tuning of large language models, enabling effective adaptation with a small number of trainable parameters. However, its reliance on linear low-rank projections restricts adaptation to linear subspaces, which can...

效率与系统推理理论与学习动力学OpenReview 项目页

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