Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging | Paper Citation Record

Observation dfe68859-c520-4e9d-8a11-75d03f3c10f3 · outbound

This paper cites Editing Models with Task Arithmetic.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Editing Models with Task Arithmetic

Reference 1

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This paper cites arXiv preprint arXiv:2601.21598 , year=.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2601.21598 , year=

Reference 2

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This paper cites arXiv preprint arXiv:2511.06411 , year=.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2511.06411 , year=

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This paper cites Advances in neural information processing systems , volume=.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Advances in neural information processing systems , volume=

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This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Understanding R1-Zero-Like Training: A Critical Perspective

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2510.10603 , year=

Reference 6

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This paper cites arXiv preprint arXiv:2603.12228 , year=.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2603.12228 , year=

Reference 7

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This paper cites Reasoning Resides in Layers: Restoring Temporal Reasoning in Video-Language Models with Layer-Selective Merging.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Reasoning Resides in Layers: Restoring Temporal Reasoning in Video-Language Models with Layer-Selective Merging

Reference 8

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This paper cites From System 1 to System 2: A Survey of Reasoning Large Language Models.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging From System 1 to System 2: A Survey of Reasoning Large Language Models

Reference 9

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Forty-first International Conference on Machine Learning , year=

Reference 10

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This paper cites Nature Machine Intelligence , volume=.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Nature Machine Intelligence , volume=

Reference 11

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This paper cites Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning

Reference 12

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This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 13

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging , author=

Reference 14

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This paper cites Training Verifiers to Solve Math Word Problems.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Training Verifiers to Solve Math Word Problems

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging 2025 , eprint=

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Unresolved cited work

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2604.01499 , year=

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This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 19

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This paper cites Notion Blog , volume=.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Notion Blog , volume=

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2508.08221 , year=

Reference 21

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This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 22

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2602.02710 , year=

Reference 23

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2512.23165 , year=

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This paper cites Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging

Reference 25

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2510.08987 , year=

Reference 26

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2601.20861 , year=

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This paper cites Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Reference 28

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging ESSAM: A Novel Competitive Evolution Strategies Approach to Reinforcement Learning for Memory Efficient LLMs Fine-Tuning

Reference 29

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2511.16652 , year=

Reference 30

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This paper cites MiniCPM-V: A GPT-4V Level MLLM on Your Phone.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging MiniCPM-V: A GPT-4V Level MLLM on Your Phone

Reference 31

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Advances in neural information processing systems , volume=

Reference 32

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Efficient Inference for Large Reasoning Models: A Survey

Reference 33

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Reasoning-CV: Fine-tuning Powerful Reasoning LLMs for Knowledge-Assisted Claim Verification

Reference 34

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging MobileRAG: A Fast, Memory-Efficient, and Energy-Efficient Method for On-Device RAG

Reference 35

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Proceedings of the 26th annual international conference on machine learning , pages=

Reference 36

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Proceedings of the 62nd annual meeting of the association for computational linguistics (volume 3: system demonstrations) , pages=

Reference 37

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging International Conference on Learning Representations , volume=

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Proceedings of the 2021 conference of the North American chapter of the association for computational linguistics: human language technologies , pages=

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Proceedings of the 2015 conference on empirical methods in natural language processing , pages=

Reference 40

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging International conference on machine learning , pages=

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Evolutionary computation , volume=

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging HybridFlow: A Flexible and Efficient RLHF Framework

Reference 43

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2512.05760 , year=

Reference 44

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging arXiv preprint arXiv:2507.04453 , year=

Reference 45

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging ACM Computing Surveys , volume=

Reference 46

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging From Explicit CoT to Implicit CoT: Learning to Internalize CoT Step by Step

Reference 48

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Whoever Started the Interference Should End It: Guiding Data-Free Model Merging via Task Vectors

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design

Reference 51

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Advances in Neural Information Processing Systems , volume=

Reference 52

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This paper cites CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention

Reference 53

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This paper cites DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems

Reference 54

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:15:08.211179Z

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This paper cites IEEE Transactions on Intelligent Transportation Systems , volume=.

Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging IEEE Transactions on Intelligent Transportation Systems , volume=

Reference 56

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Reference 57

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Reference 58

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Program Synthesis with Large Language Models

Reference 60

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Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging Evaluating Large Language Models Trained on Code

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