Hanqi Yan

52 papers A* 9A 1Journal 29Unranked 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
AutoMonitor-Bench: Evaluating the Reliability of LLM-Based Misbehavior Monitor.
CoRR
Shu Yang, Jingyu Hu, Tong Li, Hanqi Yan, Wenxuan Wang, Di Wang
2026 A* conf
Beyond Perplexity: Let the Reader Select Retrieval Summaries via Spectrum Projection Score.
AAAI
Zhanghao Hu, Qinglin Zhu, Siya Qi, Yulan He, Hanqi Yan, Lin Gui
2026 J jnl
Beyond RAG for Agent Memory: Retrieval by Decoupling and Aggregation.
CoRR
Zhanghao Hu, Qinglin Zhu, Hanqi Yan, Yulan He, Lin Gui
2026 J jnl
Context Compression via Explicit Information Transmission.
CoRR
Jiangnan Ye, Hanqi Yan, Zhenyi Shen, Heng Chang, Ye Mao, Yulan He
2026 J jnl
Not All Code Is Equal: A Data-Centric Study of Code Complexity and LLM Reasoning.
CoRR
Lukas Twist, Shu Yang, Hanqi Yan, Jingzhi Gong, Di Wang, Helen Yannakoudakis, Jie M. Zhang
2026 J jnl
Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding.
CoRR
Yanzheng Xiang, Lan Wei, Yizhen Yao, Qinglin Zhu, Hanqi Yan, Chen Jin, Philip Alexander Teare, Dandan Zhang, Lin Gui, Amrutha Saseendran, Yulan He
2025 — conf
Beyond Prompting: An Efficient Embedding Framework for Open-Domain Question Answering.
ACL (1)
Zhanghao Hu, Hanqi Yan, Qinglin Zhu, Zhenyi Shen, Yulan He, Lin Gui
2025 J jnl
Beyond Prompting: An Efficient Embedding Framework for Open-Domain Question Answering.
CoRR
Zhanghao Hu, Hanqi Yan, Qingling Zhu, Zhenyi Shen, Yulan He, Lin Gui
2025 A* conf
CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation.
EMNLP
Zhenyi Shen, Hanqi Yan, Linhai Zhang, Zhanghao Hu, Yali Du, Yulan He
2025 J jnl
CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation.
CoRR
Zhenyi Shen, Hanqi Yan, Linhai Zhang, Zhanghao Hu, Yali Du, Yulan He
2025 A* conf
Constrain Alignment with Sparse Autoencoders.
ICML
Qingyu Yin, Chak Tou Leong, Hongbo Zhang, Minjun Zhu, Hanqi Yan, Qiang Zhang, Yulan He, Wenjie Li, Jun Wang, Yue Zhang, Linyi Yang
2025 — conf
Drift: Enhancing LLM Faithfulness in Rationale Generation via Dual-Reward Probabilistic Inference.
ACL (1)
Jiazheng Li, Hanqi Yan, Yulan He
2025 — conf
GraphMind: Interactive Novelty Assessment System for Accelerating Scientific Discovery.
EMNLP (System Demonstrations)
Italo Luis da Silva, Hanqi Yan, Lin Gui, Yulan He
2025 J jnl
GraphMind: Interactive Novelty Assessment System for Accelerating Scientific Discovery.
CoRR
Italo Luis da Silva, Hanqi Yan, Lin Gui, Yulan He
2025 — conf
Position: LLMs Need a Bayesian Meta-Reasoning Framework for More Robust and Generalizable Reasoning.
ICML (Position Papers)
Hanqi Yan, Linhai Zhang, Jiazheng Li, Zhenyi Shen, Yulan He
2025 J jnl
SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research Papers.
CoRR
Yanzheng Xiang, Hanqi Yan, Shuyin Ouyang, Lin Gui, Yulan He
2025 A* conf
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration.
ICML
Qinglin Zhu, Runcong Zhao, Hanqi Yan, Yulan He, Yudong Chen, Lin Gui
2025 J jnl
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration.
CoRR
Qinglin Zhu, Runcong Zhao, Hanqi Yan, Yulan He, Yudong Chen, Lin Gui
2025 J jnl
Spectrum Projection Score: Aligning Retrieved Summaries with Reader Models in Retrieval-Augmented Generation.
CoRR
Zhanghao Hu, Qinglin Zhu, Siya Qi, Yulan He, Hanqi Yan, Lin Gui
2025 J jnl
The Multi-Faceted Monosemanticity in Multimodal Representations.
CoRR
Hanqi Yan, Xiangxiang Cui, Lu Yin, Paul Pu Liang, Yulan He, Yifei Wang
2025 J jnl
When Thinking Backfires: Mechanistic Insights Into Reasoning-Induced Misalignment.
CoRR
Hanqi Yan, Hainiu Xu, Siya Qi, Shu Yang, Yulan He
2024 — conf
Addressing Order Sensitivity of In-Context Demonstration Examples in Causal Language Models.
ACL (Findings)
Yanzheng Xiang, Hanqi Yan, Lin Gui, Yulan He
2024 J jnl
Addressing Order Sensitivity of In-Context Demonstration Examples in Causal Language Models.
CoRR
Yanzheng Xiang, Hanqi Yan, Lin Gui, Yulan He
2024 J jnl
Counterfactual Generation with Identifiability Guarantees.
CoRR
Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang
2024 J jnl
Direct Preference Optimization Using Sparse Feature-Level Constraints.
CoRR
Qingyu Yin, Chak Tou Leong, Hongbo Zhang, Minjun Zhu, Hanqi Yan, Qiang Zhang, Yulan He, Wenjie Li, Jun Wang, Yue Zhang, Linyi Yang
2024 A* conf
Encourage or Inhibit Monosemanticity? Revisit Monosemanticity from a Feature Decorrelation Perspective.
EMNLP
Hanqi Yan, Yanzheng Xiang, Guangyi Chen, Yifei Wang, Lin Gui, Yulan He
2024 J jnl
Encourage or Inhibit Monosemanticity? Revisit Monosemanticity from a Feature Decorrelation Perspective.
CoRR
Hanqi Yan, Yanzheng Xiang, Guangyi Chen, Yifei Wang, Lin Gui, Yulan He
2024 J jnl
Explainable Recommender With Geometric Information Bottleneck.
IEEE Trans. Knowl. Data Eng.
Hanqi Yan, Lin Gui, Menghan Wang, Kun Zhang, Yulan He
2024 J jnl
Mirror: A Multiple-perspective Self-Reflection Method for Knowledge-rich Reasoning.
CoRR
Hanqi Yan, Qinglin Zhu, Xinyu Wang, Lin Gui, Yulan He
2024 — conf
Mirror: Multiple-perspective Self-Reflection Method for Knowledge-rich Reasoning.
ACL (1)
Hanqi Yan, Qinglin Zhu, Xinyu Wang, Lin Gui, Yulan He
2024 A* conf
The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysis.
EMNLP
Yuxiang Zhou, Jiazheng Li, Yanzheng Xiang, Hanqi Yan, Lin Gui, Yulan He
2024 A* conf
Weak Reward Model Transforms Generative Models into Robust Causal Event Extraction Systems.
EMNLP
Italo Luis da Silva, Hanqi Yan, Lin Gui, Yulan He
2024 J jnl
Weak Reward Model Transforms Generative Models into Robust Causal Event Extraction Systems.
CoRR
Italo Luis da Silva, Hanqi Yan, Lin Gui, Yulan He
2023 A* conf
Counterfactual Generation with Identifiability Guarantees.
NeurIPS
Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang
2023 — conf
Distinguishability Calibration to In-Context Learning.
EACL (Findings)
Hongjing Li, Hanqi Yan, Yanran Li, Li Qian, Yulan He, Lin Gui
2023 J jnl
Distinguishability Calibration to In-Context Learning.
CoRR
Hongjing Li, Hanqi Yan, Yanran Li, Li Qian, Yulan He, Lin Gui
2023 J jnl
Explainable Recommender with Geometric Information Bottleneck.
CoRR
Hanqi Yan, Lin Gui, Menghan Wang, Kun Zhang, Yulan He
2023 J jnl
The Mystery and Fascination of LLMs: A Comprehensive Survey on the Interpretation and Analysis of Emergent Abilities.
CoRR
Yuxiang Zhou, Jiazheng Li, Yanzheng Xiang, Hanqi Yan, Lin Gui, Yulan He
2023 J jnl
Tracking Brand-Associated Polarity-Bearing Topics in User Reviews.
CoRR
Runcong Zhao, Lin Gui, Hanqi Yan, Yulan He
2023 J jnl
Tracking Brand-Associated Polarity-Bearing Topics in User Reviews.
Trans. Assoc. Comput. Linguistics
Runcong Zhao, Lin Gui, Hanqi Yan, Yulan He
2022 J jnl
Addressing Token Uniformity in Transformers via Singular Value Transformation.
CoRR
Hanqi Yan, Lin Gui, Wenjie Li, Yulan He
2022 A conf
Addressing token uniformity in transformers via singular value transformation.
UAI
Hanqi Yan, Lin Gui, Wenjie Li, Yulan He
2022 — ed.
Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022, Online only, November 20-23, 2022
AACL/IJCNLP (Findings)
Yulan He, Heng Ji, Yang Liu, Sujian Li, Chia-Hui Chang, Soujanya Poria, Chenghua Lin, Wray L. Buntine, Maria Liakata, Hanqi Yan, Zonghan Yan, Sebastian Ruder, Xiaojun Wan, Miguel Arana-Catania, Zhongyu Wei, Hen-Hsen Huang, Jheng-Long Wu, Min-Yuh Day, Pengfei Liu, Ruifeng Xu
2022 J jnl
Hierarchical Interpretation of Neural Text Classification.
Comput. Linguistics
Hanqi Yan, Lin Gui, Yulan He
2022 J jnl
Hierarchical Interpretation of Neural Text Classification.
CoRR
Hanqi Yan, Lin Gui, Yulan He
2022 — ed.
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, AACL/IJCNLP 2022 - Student Research Workshop, Online, November 20, 2022
AACL/IJCNLP 2022 (Student Research Workshop)
Hanqi Yan, Zonghan Yang, Sebastian Ruder, Xiaojun Wan
2022 — ed.
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, AACL/IJCNLP 2022 - Volume 1: Long Papers, Online Only, November 20-23, 2022
AACL/IJCNLP (1)
Yulan He, Heng Ji, Yang Liu, Sujian Li, Chia-Hui Chang, Soujanya Poria, Chenghua Lin, Wray L. Buntine, Maria Liakata, Hanqi Yan, Zonghan Yan, Sebastian Ruder, Xiaojun Wan, Miguel Arana-Catania, Zhongyu Wei, Hen-Hsen Huang, Jheng-Long Wu, Min-Yuh Day, Pengfei Liu, Ruifeng Xu
2022 — ed.
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, AACL/IJCNLP 2022 - Volume 2: Short Papers, Online only, November 20-23, 2022
AACL/IJCNLP (2)
Yulan He, Heng Ji, Yang Liu, Sujian Li, Chia-Hui Chang, Soujanya Poria, Chenghua Lin, Wray L. Buntine, Maria Liakata, Hanqi Yan, Zonghan Yan, Sebastian Ruder, Xiaojun Wan, Miguel Arana-Catania, Zhongyu Wei, Hen-Hsen Huang, Jheng-Long Wu, Min-Yuh Day, Pengfei Liu, Ruifeng Xu
2021 — conf
Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction.
ACL/IJCNLP (1)
Hanqi Yan, Lin Gui, Gabriele Pergola, Yulan He
2021 J jnl
Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction.
CoRR
Hanqi Yan, Lin Gui, Gabriele Pergola, Yulan He
2020 A* conf
Reinforcement Learning based Recommendation with Graph Convolutional Q-network.
SIGIR
Yu Lei, Hongbin Pei, Hanqi Yan, Wenjie Li
2019 — conf
LexicalAT: Lexical-Based Adversarial Reinforcement Training for Robust Sentiment Classification.
EMNLP/IJCNLP (1)
Jingjing Xu, Liang Zhao, Hanqi Yan, Qi Zeng, Yun Liang, Xu Sun
test1.txt
← Index test1.txt plaintext
Truncated preview: showing the first 16384 bytes out of 43286155 total.
{'decompiled': [{'decompiled_function_hash': '1f0dd5f0fe1f0f28d39c8f98bf5eb5b06a98405389873053efd1df2f3ca12179', 'decompiled_function': 'bool z\n\nif (arg3 == *arg2)\n    *arg2 = arg1\n    z = true\nelse\n    *arg2\n    z = false\n\nint64_t result\nresult.b = z\nreturn result', 'decompiled_function_name': 'sync/atomic.CompareAndSwapUintptr', 'decompiled_function_prototype': 'int64_t sync/atomic.CompareAndSwapUintptr(int64_t arg1, int64_t* arg2 @ rax, int64_t arg3 @ rbx)', 'decompiled_function_address': 4198528, 'function_type': 'USER', 'functions_caller': [], 'functions_call': [], 'flattened_score': 0.0, 'mba_score': 0.0, 'disassembled_function_hash': '09e03a03d3a93deea76172fc49c83d407cff050807a0e40d5b25b8848182f060'}, {'decompiled_function_hash': '02b054c1841b6532a667e3e61f8c3363dffbc0893dc9cee31e16e6438a6b32ee', 'decompiled_function': 'int64_t rcx = data_6531e8\nint64_t* internal/abi.kindNames_1 = internal/abi.kindNames\n\nif (arg1 s>= rcx)\n    if (rcx u> 0)\n        internal/abi.kindNames_1[1]\n        return *internal/abi.kindNames_1\n    \n    runtime.panicIndex(0)\nelse if (arg1 u< rcx)\n    internal/abi.kindNames_1[arg1 * 2 + 1]\n    return internal/abi.kindNames_1[arg1 * 2]\n\nruntime.panicIndexU()\nbreakpoint', 'decompiled_function_name': 'internal/abi.Kind.String', 'decompiled_function_prototype': 'int64_t internal/abi.Kind.String(int64_t arg1 @ rax)', 'decompiled_function_address': 4198720, 'function_type': 'USER', 'functions_caller': [], 'functions_call': ['runtime.panicIndex(0)', 'runtime.panicIndexU()'], 'flattened_score': 0.0, 'mba_score': 0.0, 'disassembled_function_hash': 'ba0c8a4a2a408f300d085876a7263294d4b54f4214bc693afe46b9e8378cbf31'}, {'decompiled_function_hash': '03a962adee69ce6e97437b8250ca1e912d9f55f0c17a29845e7e55e9544b5fa9', 'decompiled_function': 'if ((zx.q(*(arg1 + 0x17)) & 0x1f) != 0x11)\n    return 0\n\nreturn *(arg1 + 0x40)', 'decompiled_function_name': 'internal/abi.(*Type).Len', 'decompiled_function_prototype': 'int64_t internal/abi.(*Type).Len(void* arg1 @ rax)', 'decompiled_function_address': 4198816, 'function_type': 'USER', 'functions_caller': [], 'functions_call': [], 'flattened_score': 0.0, 'mba_score': 0.3333333333333333, 'disassembled_function_hash': 'a2843f9a81f7822d6b6b55e43df329ee31eed92dae8dc41ca991d56d7632c1b9'}, {'decompiled_function_hash': 'd782b427b58ad2cf84c6a7c609d1d872f14db0788919434f18e9c183125af6d3', 'decompiled_function': 'void* rsi_4\n\nif ((*(arg1 + 0x14) & 1) == 0)\n    rsi_4 = nullptr\nelse\n    int64_t rsi_3 = (zx.q(*(arg1 + 0x17)) & 0x1f) - 0x11\n    \n    if (rsi_3 u<= 8)\n        jump(internal/abi.(*Type).ExportedMethods.jump7[rsi_3])\n    \n    rsi_4 = arg1 + 0x30\n\nif (rsi_4 == 0)\n    return 0\n\nuint64_t rdx = zx.q(*(rsi_4 + 6))\n\nif (rdx.w == 0)\n    return nullptr\n\nif (rdx u<= 0x10000)\n    return rsi_4 + zx.q(*(rsi_4 + 8))\n\nruntime.panicSlice3Alen()\nbreakpoint', 'decompiled_function_name': 'internal/abi.(*Type).ExportedMethods', 'decompiled_function_prototype': 'void* internal/abi.(*Type).ExportedMethods(void* arg1 @ rax)', 'decompiled_function_address': 4198880, 'function_type': 'USER', 'functions_caller': [], 'functions_call': ['jump(internal/abi.(*Type).ExportedMethods.jump7[rsi_3])', 'runtime.panicSlice3Alen()'], 'flattened_score': 0.0, 'mba_score': 0.125, 'disassembled_function_hash': 'e2558c9cf3ebac3a28dff29dcc0b8918965ca5091e4d5e0361af301ebc9d7fba'}, {'decompiled_function_hash': '407d3d24d10ffe65a17c09aa88e6d7283d00fcdd9df10741af968c91841cc9b2', 'decompiled_function': 'while (&__return_addr u<= *(arg3 + 0x10))\n    runtime.morestack_noctxt.abi0()\n\nuint64_t rcx_1 = zx.q(*(arg1 + 0x17)) & 0x1f\n\nif (rcx_1 == 0x14)\n    return *(arg1 + 0x40)\n\ninternal/abi.(*Type).ExportedMethods(arg1, rcx_1)\nreturn arg2', 'decompiled_function_name': 'internal/abi.(*Type).NumMethod', 'decompiled_function_prototype': 'int64_t internal/abi.(*Type).NumMethod(void* arg1 @ rax, int64_t arg2 @ rbx, void* arg3 @ r14)', 'decompiled_function_address': 4199072, 'function_type': 'USER', 'functions_caller': [], 'functions_call': ['internal/abi.(*Type).ExportedMethods(arg1, rcx_1)', 'runtime.morestack_noctxt.abi0()'], 'flattened_score': 1.0, 'mba_score': 0.14285714285714285, 'disassembled_function_hash': '270037f0c8addf478f25bc075eb0dc05fc54dff87fba6dff63ab8d0555e4929a'}, {'decompiled_function_hash': '9f2a44ad4622a0e2d0e1b439b1d46754301fd5f7060b91e3766482b1383494da', 'decompiled_function': 'if (arg1 == 0)\n    return 0\n\nint64_t rcx = 0\nint64_t rdx = 0\n\nwhile (true)\n    int64_t rbx_2 = rcx * 7\n    *(arg1 + rcx + 1)\n    \n    if (rbx_2 s< 0)\n        runtime.panicshift()\n        breakpoint\n    \n    uint32_t rdi_3 = zx.d(*(arg1 + rcx + 1))\n    rdx += (zx.q(rdi_3) & 0x7f) << rbx_2.b & sbb.q(rbx_2, rbx_2, rbx_2 u< 0x40)\n    \n    if ((rdi_3.b & 0x80) == 0)\n        break\n    \n    rcx += 1\n\nint64_t rcx_1\n\nif (rdx != 1)\n    rcx_1 = 0\nelse\n    rcx_1.b = *(arg1 + 2) == 0x5f\n\nreturn zx.q(rcx_1.d)', 'decompiled_function_name': 'internal/abi.Name.IsBlank', 'decompiled_function_prototype': 'uint64_t internal/abi.Name.IsBlank(void* arg1 @ rax)', 'decompiled_function_address': 4199168, 'function_type': 'USER', 'functions_caller': [], 'functions_call': ['runtime.panicshift()'], 'flattened_score': 0.7692307692307693, 'mba_score': 0.05, 'disassembled_function_hash': '7a693574e5a54de381301402832a96b61c8f4d2a2671d8150e93fb29f8692e0f'}, {'decompiled_function_hash': 'aaadbfaff6f26ed203060269065749f25f44d295aadde2386ab73f8c4a5dd767', 'decompiled_function': 'while (true)\n    int64_t* rsp\n    \n    if (rsp u> *(arg3 + 0x10))\n        *(rsp - 8) = arg2\n        rsp -= 8\n        arg2 = rsp\n        \n        if (arg1 == 0)\n            *rsp\n            return 0\n        \n        void* rcx_1 = nullptr\n        int64_t rdx_1 = 0\n        \n        while (true)\n            void* rsi_2 = rcx_1 * 7\n            *(rcx_1 + arg1 + 1)\n            \n            if (rsi_2 s< 0)\n                break\n            \n            uint32_t r8_3 = zx.d(*(rcx_1 + arg1 + 1))\n            rdx_1 += (zx.q(r8_3) & 0x7f) << rsi_2.b & sbb.q(rsi_2, rsi_2, rsi_2 u< 0x40)\n            \n            if ((r8_3.b & 0x80) == 0)\n                if (rdx_1 s>= 0)\n                    int64_t rcx_4 = neg.q(rcx_1 + arg1 + 2)\n                    \n                    if (rcx_4 u>= rdx_1)\n                        *rsp\n                        return rcx_1 + arg1 + 2\n                    \n                    if (rcx_1 + arg1 != -2)\n                        runtime.panicunsafestringlen(rcx_4)\n                    \n                    runtime.panicunsafestringnilptr()\n                \n                runtime.panicunsafestringlen()\n                break\n            \n            rcx_1 += 1\n        \n        arg1 = runtime.panicshift()\n    \n    rsp[1] = arg1\n    runtime.morestack_noctxt.abi0()\n    arg1 = rsp[1]', 'decompiled_function_name': 'internal/abi.Name.Name', 'decompiled_function_prototype': 'void* internal/abi.Name.Name(int64_t arg1 @ rax, int64_t* arg2 @ rbp, void* arg3 @ r14)', 'decompiled_function_address': 4199296, 'function_type': 'USER', 'functions_caller': [], 'functions_call': ['runtime.panicunsafestringlen(rcx_4)', 'runtime.panicunsafestringnilptr()', 'runtime.panicunsafestringlen()', 'arg1 = runtime.panicshift()', 'runtime.morestack_noctxt.abi0()'], 'flattened_score': 1.0, 'mba_score': 0.029411764705882353, 'disassembled_function_hash': '21ad7fe65b5907f2e2bd82711c3d5cda50e2cda11dd6cb13e472a1879a0f5ee0'}, {'decompiled_function_hash': '6bc616921202fbee6edcbe36548ca6c0123ae51ecb86c0eea217f3889c581d25', 'decompiled_function': 'while (true)\n    int64_t* rsp\n    \n    if (rsp u> *(arg3 + 0x10))\n        *(rsp - 8) = arg2\n        rsp -= 8\n        arg2 = rsp\n        \n        if ((*arg1 & 2) == 0)\n            *rsp\n            return 0\n        \n        void* rcx_1 = nullptr\n        void* rdx_2 = nullptr\n        \n        while (true)\n            void* rsi_2 = rcx_1 * 7\n            *(rcx_1 + arg1 + 1)\n            \n            if (rsi_2 s< 0)\n                break\n            \n            uint32_t r8_3 = zx.d(*(rcx_1 + arg1 + 1))\n            rdx_2 += (zx.q(r8_3) & 0x7f) << rsi_2.b & sbb.q(rsi_2, rsi_2, rsi_2 u< 0x40)\n            \n            if ((r8_3.b & 0x80) == 0)\n                int64_t rcx_3 = 0\n                int64_t rbx_3 = 0\n                \n                while (true)\n                    void* rsi_4 = rdx_2 + rcx_1 + rcx_3\n                    int64_t rdi_3 = rcx_3 * 7\n                    *(arg1 + rsi_4 + 2)\n                    \n                    if (rdi_3 s< 0)\n                        break\n                    \n                    uint32_t r8_9 = zx.d(*(arg1 + rsi_4 + 2))\n                    rbx_3 += (zx.q(r8_9) & 0x7f) << rdi_3.b & sbb.q(rdi_3, rdi_3, rdi_3 u< 0x40)\n                    \n                    if ((r8_9.b & 0x80) == 0)\n                        if (rbx_3 s>= 0)\n                            int64_t rcx_6 = neg.q(arg1 + rsi_4 + 3)\n                            \n                            if (rcx_6 u>= rbx_3)\n                                *rsp\n                                return arg1 + rsi_4 + 3\n                            \n                            if (arg1 + rsi_4 != -3)\n                                runtime.panicunsafestringlen(rcx_6)\n                            \n                            runtime.panicunsafestringnilptr()\n                        \n                        runtime.panicunsafestringlen()\n                        break\n                    \n                    rcx_3 += 1\n                \n                runtime.panicshift()\n                break\n            \n            rcx_1 += 1\n        \n        arg1 = runtime.panicshift()\n    \n    rsp[1] = arg1\n    runtime.morestack_noctxt.abi0()\n    arg1 = rsp[1]', 'decompiled_function_name': 'internal/abi.Name.Tag', 'decompiled_function_prototype': 'void* internal/abi.Name.Tag(char* arg1 @ rax, int64_t* arg2 @ rbp, void* arg3 @ r14)', 'decompiled_function_address': 4199488, 'function_type': 'USER', 'functions_caller': [], 'functions_call': ['runtime.panicunsafestringlen(rcx_6)', 'runtime.panicunsafestringnilptr()', 'runtime.panicunsafestringlen()', 'runtime.panicshift()', 'arg1 = runtime.panicshift()', 'runtime.morestack_noctxt.abi0()'], 'flattened_score': 1.0, 'mba_score': 0.041666666666666664, 'disassembled_function_hash': '0621c0c17af04d429b48b7855fd82627f2e835ec864eaa49d0de3183fd3d9fbf'}, {'decompiled_function_hash': '917d57a1b59aad9ee7b1197909e67f4ee8d39a0d26f2390ceacbbc54bde37a43', 'decompiled_function': 'while (true)\n    void* rsp\n    \n    if (rsp - 0x30 u> *(arg9 + 0x10))\n        *(rsp - 8) = arg6\n        arg6 = rsp - 8\n        rsp -= 0xb0\n        *(rsp + 0xb8) = arg4\n        *(rsp + 0xc8) = arg1\n        \n        if (arg5 s< 0x20000000)\n            if (arg8 s< 0x20000000)\n                __builtin_memset(rsp + 0x84, 0, 0x14)\n                int64_t rdx = arg5\n                int64_t r9_1 = 0\n                \n                while (true)\n                    char r10_2 = arg5.b\n                    arg5 s>>= 7\n                    char r10_3 = r10_2 & 0x7f\n                    \n                    if (arg5 == 0)\n                        if (r9_1 u< 0xa)\n                            *(rsp + r9_1 + 0x8e) = r10_3\n                            int64_t rbx = arg8\n                            int64_t r10_4 = 0\n                            \n                            while (true)\n                                char r11_2 = arg8.b\n                                arg8 s>>= 7\n                                char r11_3 = r11_2 & 0x7f\n                                \n                                if (arg8 == 0)\n                                    if (r10_4 u< 0xa)\n                                        *(rsp + r10_4 + 0x84) = r11_3\n                                        int64_t r11_4 = rdx + r9_1\n                                        int64_t r12_3\n                                        \n                                        if (rbx == 0)\n                                            r12_3 = r9_1 + rdx + 2\n                                        else\n                                            r12_3 = rbx + r10_4 + r11_4 + 3\n                                            arg7 |= 2\n                                        \n                                        *(rsp + 0x78) = rdx\n                                        *(rsp + 0x48) = r9_1 + rdx + 2\n                                        *(rsp + 0x70) = rbx\n                                        *(rsp + 0xb8) = arg4\n                                        *(rsp + 0xc8) = arg1\n                                        *(rsp + 0x68) = r11_4\n                                        *(rsp + 0x50) = r10_4\n                                        *(rsp + 0x58) = r9_1\n                                        \n                                        if (arg3 != 0)\n                                            arg7 |= 8\n                                        \n                                        *(rsp + 0x3f) = arg7.b\n                                        *(rsp + 0x60) = r12_3\n                                        char* result = runtime.makeslice(r12_3)\n                                        void* rcx_1 = *(rsp + 0x60)\n                                        \n                                        if (rcx_1 u> 0)\n                                            *(rsp + 0xa0) = result\n                                            *result = *(rsp + 0x3f)\n                                            void* rsi = rcx_1 - 1\n                                            uint64_t rdx_6 = (zx.q((neg.q(rcx_1 - 1) s>> 0x3f).d) & 1) + result\n                                            void* rdi_2 = *(rsp + 0x58)\n                                            \n                                            if (rdi_2 + 1 s< rsi)\n                                                rsi = rdi_2 + 1\n                                            \n                                            if (rsp + 0x8e != rdx_6)\n                                                runtime.memmove(rsi, rdx_6, rsp + 0x8e)\n                                                result = *(rsp + 0xa0)\n                                                rcx_1 = *(rsp + 0x60)\n                                                rdi_2 = *(rsp + 0x58)\n                                            \n                                            if (rcx_1 u>= rdi_2 + 2)\n                                                void* rdi_3 = rcx_1 - rdi_2 - 2\n                                                void* rdx_9 = ((rdi_2 + 2) & neg.q(rcx_1 - rdi_2 - 2) s>> 0x3f) + result\n                                                void* rsi_6 = *(rsp + 0x78)\n                                                \n                                                if (rsi_6 s< rdi_3)\n                                                    rdi_3 = rsi_6\n                                                \n                                                int128_t* rbx_3 = *(rsp + 0xb8)\n                                                void* rdx_10\n                                                bool cond:0_1\n                                                \n                                                if (rbx_3 != rdx_9)\n                                                    runtime.memmove(rdi_3, rdx_9, rbx_3)\n                                                    rdx_10 = *(rsp + 0x70)\n                                                    cond:0_1 = rdx_10 == 0\n                                                    result = *(rsp + 0xa0)\n                                                    rcx_1 = *(rsp + 0x60)\n                                                else\n                                                    rdx_10 = *(rsp + 0x70)\n                                                    cond:0_1 = rdx_10 == 0\n                                                \n                                                if (cond:0_1)\n                                                    *(rsp + 0xa8)\n                                                    return result\n                                                \n                                                uint64_t rsi_7 = *(rsp + 0x48)\n