---
title: "Bing Qin — papers of 2026 — 11 papers, the most cited first"
description: "Bing Qin — papers of 2026: 11 papers on Elamur Research, the most cited first — what each work is about in our own words."
canonical: "https://research.elamur.ai/free/en/authors/bing-qin/year/2026/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/bing-qin/year/2026/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Bing Qin](https://md.research.elamur.ai/free/en/authors/bing-qin/) / 2026

# Bing Qin — papers of 2026 — 11 papers, the most cited first

11 papers · [all years of Bing Qin](https://md.research.elamur.ai/free/en/authors/bing-qin/#years)

**[Culture-Aware Machine Translation in Large Language Models: Benchmarking and Investigation](https://md.research.elamur.ai/free/en/papers/yuan-2026-culture-aware-machine-translation-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zekun Yuan, Yangfan Ye, Xiaocheng Feng, et al.*2026 · 2 citations*

**[Psychological Counseling Cannot Be Achieved Overnight: Automated Psychological Counseling Through Multi-Session Conversations](https://md.research.elamur.ai/free/en/papers/wang-2026-psychological-counseling-cannot-be-achieved/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bichen Wang, Junzhe Wang, Yixin Sun, et al.*2026 · 2 citations*

**[MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward Optimization](https://md.research.elamur.ai/free/en/papers/zhao-2026-maestro-meta-learning-adaptive-estimation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Zhao, Hepeng Wang, Xiao Ding, et al.*2026 · 1 citation*

**[On Safety Risks in Experience-Driven Self-Evolving Agents](https://md.research.elamur.ai/free/en/papers/zhao-2026-safety-risks-experience-driven-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weixiang Zhao, Yichen Zhang, Yingshuo Wang, et al.*2026 · 1 citation*

**[TEA-Bench: A Systematic Benchmarking of Tool-enhanced Emotional Support Dialogue Agent](https://md.research.elamur.ai/free/en/papers/sui-2026-tea-bench-systematic-benchmarking-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingyu Sui, Yanyan Zhao, Yulin Hu, et al.*2026 · 1 citation*

**[x1: Learning to Think Adaptively Across Languages and Cultures](https://md.research.elamur.ai/free/en/papers/ye-2026-x1-learning-think-adaptively-across/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangfan Ye, Xiaocheng Feng, Xiachong Feng, et al.*2026 · 1 citation*

**[Fine-Mem: Fine-Grained Feedback Alignment for Long-Horizon Memory Management](https://md.research.elamur.ai/free/en/papers/ma-2026-fine-mem-fine-grained-feedback/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weitao Ma, Xiaocheng Feng, Lei Huang, et al.*2026*

**[From Implicit Graph Encoding to Explicit Evidence: A Training-Free LLM Framework for Temporal Knowledge Graph Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2026-implicit-graph-encoding-explicit-evidence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guo Tang, Ke Cheng, Huiming Fan, et al.*2026*

**[Large Language Models Are Still Misled by Simple Bias Ensembles](https://md.research.elamur.ai/free/en/papers/sun-2026-large-language-models-are-still/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhouhao Sun, Zhiyuan Kan, Xiao Ding, et al.*2026*

**[MDC-Bench: A Multidisciplinary Causal Benchmark Based on Causal Structures for Evaluating Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-mdc-bench-multidisciplinary-causal-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peng Wang, Yuxiong Yan, Xiao Ding, et al.*2026*

**[PARIF: Pushing the Pareto Frontier of Instruction Following and Reasoning with Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mu-2026-parif-pushing-pareto-frontier-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rongchuan Mu, Zexin Wang, Qianyu Wang, et al.*2026*
