---
title: "Who cites Si-Qing Chen — 228 papers of our library"
description: "228 papers of the Elamur Research library cite the works of Si-Qing Chen, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/si-qing-chen/cited-by/"
---
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# Who cites Si-Qing Chen

229 citations of their works from 228 papers of our library (of the 149,439 whose bibliographies we read) · 68 with a page here, the most cited first · [← Si-Qing Chen](https://md.research.elamur.ai/free/en/authors/si-qing-chen/)

1. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models arXiv:2402.03300**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,115 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/)
2. **[LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-llmlingua-compressing-prompts-accelerated-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, et al.*2023 · 338 citations*
3. [**EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty arXiv:2401.15077**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 208 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-speculative-sampling-requires-rethinking/)
4. [**Scaling Synthetic Data Creation with 1,000,000,000 Personas arXiv:2406.20094**Tao Ge, Xin Chan, Xiaoyang Wang, et al.*2024 · 171 citations*](https://md.research.elamur.ai/free/en/papers/ge-2024-scaling-synthetic-data-creation-1/)
5. **[LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression](https://md.research.elamur.ai/free/en/papers/pan-2024-llmlingua-2-data-distillation-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, et al.*2024 · 161 citations*
6. [**LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression arXiv:2310.06839**Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-longllmlingua-accelerating-enhancing-llms-long/)
7. [**The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning arXiv:2312.01552**Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-unlocking-spell-base-llms-rethinking/)
8. [**Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing arXiv:2406.08464**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 148 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-magpie-alignment-data-synthesis-scratch/)
9. **[Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding](https://md.research.elamur.ai/free/en/papers/xia-2024-unlocking-efficiency-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Heming Xia, Zhe Yang, Qingxiu Dong, et al.*2024 · 146 citations*
10. [**Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step arXiv:2402.16906**Li Zhong, Zilong Wang, Jingbo Shang*2024 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-debug-like-human-large-language/)
11. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
12. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
13. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
14. [**LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition arXiv:2307.13269**Chengsong Huang, Qian Liu, Bill Yuchen Lin, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-lorahub-efficient-cross-task-generalization/)
15. **[TokenSkip: Controllable Chain-of-Thought Compression in LLMs](https://md.research.elamur.ai/free/en/papers/xia-2025-tokenskip-controllable-chain-thought-compression/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Heming Xia, Chak Tou Leong, Wenjie Wang, et al.*2025 · 106 citations*
16. [**Language Modeling Is Compression arXiv:2309.10668**Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, et al.*2023 · 91 citations*](https://md.research.elamur.ai/free/en/papers/deletang-2023-language-modeling-compression/)
17. [**Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention arXiv:2404.07143**Tsendsuren Munkhdalai, Manaal Faruqui, Siddharth Gopal*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/munkhdalai-2024-leave-no-context-behind-efficient/)
18. **[CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation](https://md.research.elamur.ai/free/en/papers/shen-2025-codi-compressing-chain-thought-into/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenyi Shen, Hanqi Yan, Linhai Zhang, et al.*2025 · 78 citations*
19. **[C3oT: Generating Shorter Chain-of-Thought without Compromising Effectiveness](https://md.research.elamur.ai/free/en/papers/kang-2024-c3ot-generating-shorter-chain-thought/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yu Kang, Xianghui Sun, Liangyu Chen, et al.*2024 · 66 citations*
20. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
21. **[mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding](https://md.research.elamur.ai/free/en/papers/hu-2025-mplug-docowl2-high-resolution-compressing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anwen Hu, Haiyang Xu, Liang Zhang, et al.*2025 · 62 citations*
22. [**Compressed Chain of Thought: Efficient Reasoning Through Dense Representations arXiv:2412.13171**Jeffrey Cheng, Benjamin Van Durme*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-compressed-chain-thought-efficient-reasoning/)
23. **[Instruction Pre-Training: Language Models are Supervised Multitask Learners](https://md.research.elamur.ai/free/en/papers/cheng-2024-instruction-pre-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Daixuan Cheng, Yuxian Gu, Shaohan Huang, et al.*2024 · 59 citations*
24. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
25. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)
26. **[LightThinker: Thinking Step-by-Step Compression](https://md.research.elamur.ai/free/en/papers/zhang-2025-lightthinker-thinking-step-step-compression/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jintian Zhang, Yuqi Zhu, Mengshu Sun, et al.*2025 · 50 citations*
27. [**Long Context Compression with Activation Beacon arXiv:2401.03462**Peitian Zhang, Zheng Liu, Shitao Xiao, et al.*2024 · 47 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-long-context-compression-activation-beacon/)
28. **[LongEmbed: Extending Embedding Models for Long Context Retrieval](https://md.research.elamur.ai/free/en/papers/zhu-2024-longembed-extending-embedding-models-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dawei Zhu, Liang Wang, Nan Yang, et al.*2024 · 37 citations*
29. [**MambaByte: Token-free Selective State Space Model arXiv:2401.13660**Junxiong Wang, Tushaar Gangavarapu, Jing Nathan Yan, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mambabyte-token-free-selective-state/)
30. [**On the Diversity of Synthetic Data and its Impact on Training Large Language Models arXiv:2410.15226**Hao Chen, Abdul Waheed, Xiang Li, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-diversity-synthetic-data-impact-training/)
31. **[CompAct: Compressing Retrieved Documents Actively for Question Answering](https://md.research.elamur.ai/free/en/papers/yoon-2024-compact-compressing-retrieved-documents-actively/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chanwoong Yoon, Taewhoo Lee, Hyeon Hwang, et al.*2024 · 34 citations*
32. **[500xCompressor: Generalized Prompt Compression for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2025-500xcompressor-generalized-prompt-compression-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zongqian Li, Yixuan Su, Nigel Collier*2025 · 32 citations*
33. **[OPT-Tree: Speculative Decoding with Adaptive Draft Tree Structure](https://md.research.elamur.ai/free/en/papers/wang-2025-opt-tree-speculative-decoding-adaptive/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jikai Wang, Yi Su, Juntao Li, et al.*2025 · 32 citations*
34. **[Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token Recycling](https://md.research.elamur.ai/free/en/papers/luo-2025-turning-trash-into-treasure-accelerating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianzhen Luo, Yixuan Wang, Qingfu Zhu, et al.*2025 · 22 citations*
35. **[RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation](https://md.research.elamur.ai/free/en/papers/li-2025-retrollm-empowering-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoxi Li, Jiajie Jin, Yujia Zhou, et al.*2025 · 19 citations*
36. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/)
37. **[FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling](https://md.research.elamur.ai/free/en/papers/zhao-2025-fr-spec-accelerating-large-vocabulary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weilin Zhao, Tengyu Pan, Xu Han, et al.*2025 · 15 citations*
38. **[Attention Entropy is a Key Factor: An Analysis of Parallel Context Encoding with Full-attention-based Pre-trained Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-attention-entropy-is-key-factor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhisong Zhang, Yan Wang, Xinting Huang, et al.*2025 · 14 citations*
39. [**Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual Progress arXiv:2408.14960**Ayomide Odumakinde, Daniel D'souza, Pat Verga, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/odumakinde-2024-multilingual-arbitrage-optimizing-data-pools/)
40. **[Second Language (Arabic) Acquisition of LLMs via Progressive Vocabulary Expansion](https://md.research.elamur.ai/free/en/papers/zhu-2025-second-language-arabic-acquisition-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianqing Zhu, Huang Huang, Zhihang Lin, et al.*2025 · 11 citations*
41. **[SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning](https://md.research.elamur.ai/free/en/papers/ji-2025-specvlm-enhancing-speculative-decoding-video/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yicheng Ji, Jun Zhang, Heming Xia, et al.*2025 · 10 citations*
42. **[GMSA: Enhancing Context Compression via Group Merging and Layer Semantic Alignment](https://md.research.elamur.ai/free/en/papers/tang-2026-gmsa-enhancing-context-compression-group/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiwei Tang, Zhicheng Zhang, Shunlong Wu, et al.*2026 · 8 citations*
43. **[Efficient Solutions For An Intriguing Failure of LLMs: Long Context Window Does Not Mean LLMs Can Analyze Long Sequences Flawlessly](https://md.research.elamur.ai/free/en/papers/hosseini-2025-efficient-solutions-intriguing-failure-llms/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Peyman Hosseini, Ignacio Castro, Iacopo Ghinassi, et al.*2025 · 8 citations*
44. **[Efficient Reasoning for LLMs through Speculative Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/wang-2026-efficient-reasoning-llms-through-speculative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jikai Wang, Juntao Li, Jianye Hou, et al.*2026 · 6 citations*
45. **[KNN-SSD: Enabling Dynamic Self-Speculative Decoding via Nearest Neighbor Layer Set Optimization](https://md.research.elamur.ai/free/en/papers/song-2026-knn-ssd-enabling-dynamic-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mingbo Song, Heming Xia, Jun Zhang, et al.*2026 · 5 citations*
46. **[LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification](https://md.research.elamur.ai/free/en/papers/yang-2026-longspec-long-context-lossless-speculative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Penghui Yang, Cunxiao Du, Fengzhuo Zhang, et al.*2026 · 5 citations*
47. [**Boosting Reward Model with Preference-Conditional Multi-Aspect Synthetic Data Generation arXiv:2407.16008**Jiaming Shen, Ran Xu, Yennie Jun, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/shen-2024-boosting-reward-model-preference-conditional/)
48. **[SSSD: Simply-Scalable Speculative Decoding](https://md.research.elamur.ai/free/en/papers/marzollo-2026-sssd-simply-scalable-speculative-decoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michele Marzollo, Jiawei Zhuang, Niklas Roemer, et al.*2026 · 3 citations*
49. **[Aligning Large Language Models via Fully Self-Synthetic Data](https://md.research.elamur.ai/free/en/papers/yin-2026-aligning-large-language-models-fully/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangjian Yin, Zhepei Wei, Xinyu Zhu, et al.*2026 · 2 citations*
50. **[Speculative Decoding with a Speculative Vocabulary](https://md.research.elamur.ai/free/en/papers/williams-2026-speculative-decoding-speculative-vocabulary/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Miles Williams, Young D. Kwon, Rui Li, et al.*2026 · 2 citations*
51. **[A Survey on LLM-based Conversational User Simulation](https://md.research.elamur.ai/free/en/papers/ni-2026-survey-llm-based-conversational-user/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bo Ni, Yu Wang, Leyao Wang, et al.*2026 · 1 citation*
52. **[A Teacher-Student Approach to Creating Verified Synthetic Clarification and Correction Dialogues for TableQA Tasks](https://md.research.elamur.ai/free/en/papers/poelitz-2026-teacher-student-approach-creating-verified/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Christian Poelitz, Nick McKenna*2026*
53. **[An Empirical Study of Speculative Decoding for Small Language Models](https://md.research.elamur.ai/free/en/papers/mainardi-2026-empirical-study-speculative-decoding-small/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Luca Mainardi, Selcuk Sandikci, Joaquin Vanschoren*2026*
54. **[Beyond Sample-Level Feedback: Using Reference-Level Feedback to Guide Data Synthesis](https://md.research.elamur.ai/free/en/papers/mehri-2026-beyond-sample-level-feedback-reference/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Shuhaib Mehri, Xiusi Chen, Heng Ji, et al.*2026*
55. **[Beyond Task-Level Context: Class-Conditional Context Vectors for Implicit In-Context Learning](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-task-level-context-class/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianxin Zhang, Yilu Hu, Teng Liu, et al.*2026*
56. **[CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling](https://md.research.elamur.ai/free/en/papers/zhao-2026-comet-collaborative-memory-transformer-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runsong Zhao, Shilei Liu, Jiwei Tang, et al.*2026*
57. **[Decoupled Reasoning with Implicit Fact Tokens (DRIFT): A Dual-Model Framework for Efficient Long-Context Inference](https://md.research.elamur.ai/free/en/papers/xie-2026-decoupled-reasoning-implicit-fact-tokens/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxuan Xie, Xuhong Wang*2026*
58. **[Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at Scale](https://md.research.elamur.ai/free/en/papers/tu-2026-fico-evaluating-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianhong Tu, Nicholas Crispino, Kyle Montgomery, et al.*2026*
59. **[From Logical to Computational Sparsity: Structure-Aware Block-Sparse Attention for Long-Code Completion](https://md.research.elamur.ai/free/en/papers/wang-2026-logical-computational-sparsity-structure-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanli Wang, Yanlin Wang, Bowen Zhang, et al.*2026*
60. **[Frozen LLMs are Native Decoders for High-Norm Semantic Vectors](https://md.research.elamur.ai/free/en/papers/zeng-2026-frozen-llms-are-native-decoders/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunsheng Zeng, Yongmei Tan*2026*
61. **[IterCOMP: Reasoning-aware Adaptive Prompt Compression for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/yun-2026-itercomp-reasoning-aware-adaptive-prompt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**JungMin Yun, YoungBin Kim*2026*
62. **[MTP-RL: Acceleration of Reinforcement Learning Rollouts with Policy-Aligned Multi-Token Prediction](https://md.research.elamur.ai/free/en/papers/wang-2026-mtp-rl-acceleration-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ke Wang, Aohan Zeng, Zhengxiao Du, et al.*2026*
63. **[PersonaTrace: Synthesizing Realistic Digital Footprints with LLM Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-personatrace-synthesizing-realistic-digital-footprints/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Minjia Wang, Yunfeng Wang, Xiao Ma, et al.*2026*
64. **[Read As Human: Compressing Context via Parallelizable Close Reading and Skimming](https://md.research.elamur.ai/free/en/papers/tang-2026-read-as-human-compressing-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiwei Tang, Shilei Liu, Zhicheng Zhang, et al.*2026*
65. **[RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library](https://md.research.elamur.ai/free/en/papers/wang-2026-rv-syn-rational-verifiable-mathematical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiapeng Wang, Jinhao Jiang, Zhiqiang Zhang, et al.*2026*
66. **[SpecCache: Speculative KV Cache Reuse for Efficient RAG Serving](https://md.research.elamur.ai/free/en/papers/wen-2026-speccache-speculative-kv-cache-reuse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijian Wen, Tao Zhang, Shuangwu Chen, et al.*2026*
67. **[Synthetic Instruction Generation for Low-Resource Nordic Languages: Viability and Limitations in LLM Instruction-Tuning](https://md.research.elamur.ai/free/en/papers/stenlund-2026-synthetic-instruction-generation-low-resource/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mathias Stenlund, Annika Simonsen, Lars Bungum, et al.*2026*
68. **[Training-Free Adaptive Speculative Decoding via Linguistic Priors](https://md.research.elamur.ai/free/en/papers/wang-2026-training-free-adaptive-speculative-decoding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingyi Wang, Jiaqi Huang, Zunnan Xu, et al.*2026*

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