Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:30:34.483002Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 2 inbound Pith citation observations for arXiv:2506.05333.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:30:34.483002Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T05:02:10.742834Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T22:07:26.497548Z
71 of 71 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation c3e1c9aa-981e-44c0-8247-7aadfae2d0be · outbound
Kinetics: Rethinking Test-Time Scaling Laws Generating Long Sequences with Sparse Transformers
Reference 6
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Unavailable: canonical work link unavailable.
Observation 7aa74093-ead3-4172-96c2-0b2c6f2007ea · outbound
Kinetics: Rethinking Test-Time Scaling Laws DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
Reference 8
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Unavailable: canonical work link unavailable.
Observation fc427bd5-eeff-4989-8953-b7c0243effef · outbound
Kinetics: Rethinking Test-Time Scaling Laws FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Reference 9
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Observation cf4f7989-60bf-438d-b22d-0a3edc53b3a2 · outbound
Kinetics: Rethinking Test-Time Scaling Laws FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Reference 10
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Observation f07d6d81-b35a-4556-88e7-8332586eead3 · outbound
Kinetics: Rethinking Test-Time Scaling Laws PaLM-E: An Embodied Multimodal Language Model
Reference 12
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Observation d1bb6067-0114-418b-88a9-1221a291043c · outbound
Kinetics: Rethinking Test-Time Scaling Laws GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
Reference 13
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Observation 650cc220-635d-40a7-87eb-790fc13501dd · outbound
Kinetics: Rethinking Test-Time Scaling Laws Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training
Reference 14
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Observation e8808f87-8187-46b3-9431-efdea686e8d3 · outbound
Kinetics: Rethinking Test-Time Scaling Laws GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
Reference 15
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Observation cd607189-bf74-479a-b376-433772d9fc8f · outbound
Kinetics: Rethinking Test-Time Scaling Laws Efficiently Scaling LLM Reasoning with Certaindex
Reference 16
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Observation 4d7580f4-6f6a-4601-8cf5-dec88e8761c1 · outbound
Kinetics: Rethinking Test-Time Scaling Laws The Llama 3 Herd of Models
Reference 17
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Observation 2de62fc4-092b-4c85-b8e4-cf4f2fee8dcb · outbound
Kinetics: Rethinking Test-Time Scaling Laws Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Reference 18
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Observation 319cf6c5-7717-482b-82be-f44cf6209a58 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Reference 19
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Observation 3213fc27-0748-4506-95da-a7dcec5555fc · outbound
Kinetics: Rethinking Test-Time Scaling Laws DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 20
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Observation 4e81297c-22a1-4a77-a4fa-b7a48f9c5cc0 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Training Large Language Models to Reason in a Continuous Latent Space
Reference 21
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Observation 25305e44-e40b-428b-8584-0e4fcba07bfe · outbound
Kinetics: Rethinking Test-Time Scaling Laws FastDecode: High-Throughput GPU-Efficient LLM Serving using Heterogeneous Pipelines
Reference 22
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Observation aebe028f-b09b-4c04-a860-f3b569b824fc · outbound
Kinetics: Rethinking Test-Time Scaling Laws Training Compute-Optimal Large Language Models
Reference 23
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Observation 3ff9ac0f-3a18-4191-aadb-294c016b1eaa · outbound
Kinetics: Rethinking Test-Time Scaling Laws RaaS: Reasoning-Aware Attention Sparsity for Efficient LLM Reasoning
Reference 24
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Observation e4684d1b-ae3d-4eea-adfa-6af9104d73fb · outbound
Kinetics: Rethinking Test-Time Scaling Laws Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents
Reference 25
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Observation 9de9fd75-cbd9-49e7-a418-2b2aa24193d3 · outbound
Kinetics: Rethinking Test-Time Scaling Laws OpenAI o1 System Card
Reference 26
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Observation 84c4ef5b-3e5d-487b-9efe-7f809c9c3acc · outbound
Kinetics: Rethinking Test-Time Scaling Laws LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
Reference 27
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Unavailable: canonical work link unavailable.
Observation d77db131-9fdd-4270-b3d4-b60bceb9474a · outbound
Kinetics: Rethinking Test-Time Scaling Laws Mixtral of Experts
Reference 28
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Observation 4b210226-1ba2-46f0-94b8-7912b1eae50a · outbound
Kinetics: Rethinking Test-Time Scaling Laws Hydragen: High-Throughput LLM Inference with Shared Prefixes
Reference 29
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Observation 5bc68a94-3af1-46cf-a565-c8e3bcc9ba3e · outbound
Kinetics: Rethinking Test-Time Scaling Laws Scaling Laws for Neural Language Models
Reference 30
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Observation 76025da5-ef94-4ebe-8eeb-f32aeb2484fd · outbound
Kinetics: Rethinking Test-Time Scaling Laws Transformers are rnns: Fast autoregressive transformers with linear attention
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1d234a47-80c2-4656-af6e-d0da2da7c236 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Scaling Laws for Precision
Reference 32
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Observation dd93f266-aebd-4860-898d-fa8039fe0722 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Efficient Memory Management for Large Language Model Serving with PagedAttention
Reference 33
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Observation b2454521-1f96-4c0d-9db6-19094b230dda · outbound
Kinetics: Rethinking Test-Time Scaling Laws SnapKV: LLM Knows What You are Looking for Before Generation
Reference 34
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Observation 3f9b9dfd-afad-454e-860b-10b93b92b3a4 · outbound
Kinetics: Rethinking Test-Time Scaling Laws QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving
Reference 35
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Unavailable: canonical work link unavailable.
Observation ae6aa1cd-1746-42ff-8082-e452897bb7ce · outbound
Kinetics: Rethinking Test-Time Scaling Laws KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache
Reference 36
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Observation 2d9c9fdf-5334-4227-925f-8f8302f45092 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Unresolved cited work
Reference 37
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 327fddec-e36e-4899-b590-8eb377646723 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Inference-time sparse attention with asymmetric indexing
Reference 38
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Observation 6d6b4959-a0ee-4c86-bf6a-b733d232845e · outbound
Kinetics: Rethinking Test-Time Scaling Laws SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification
Reference 39
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Unavailable: canonical work link unavailable.
Observation a848a160-e230-4f4b-b078-7d83ce424bda · outbound
Kinetics: Rethinking Test-Time Scaling Laws Accelerating Sparse Deep Neural Networks
Reference 40
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Unavailable: canonical work link unavailable.
Observation 743c9c38-d04b-4836-b21a-06d09e09ade4 · outbound
Kinetics: Rethinking Test-Time Scaling Laws CoTFormer: A Chain-of-Thought Driven Architecture with Budget-Adaptive Computation Cost at Inference
Reference 41
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Unavailable: canonical work link unavailable.
Observation a713a549-6d60-4aff-ba70-eaf95ecab93c · outbound
Kinetics: Rethinking Test-Time Scaling Laws WebGPT: Browser-assisted question-answering with human feedback
Reference 43
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Unavailable: canonical work link unavailable.
Observation c18310f8-bbd4-46bd-84b3-15266c4354f5 · outbound
Kinetics: Rethinking Test-Time Scaling Laws The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs
Reference 44
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Observation f6c34e59-d711-4541-a1ac-66f583637435 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Reference 45
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Observation 9e2c1442-353e-4789-9106-62e5ca832e3e · outbound
Kinetics: Rethinking Test-Time Scaling Laws Daniele Paliotta, Junxiong Wang, Matteo Pagliardini, Kevin Y
Reference 46
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5a899b0a-ddf2-4b4d-925a-6af2c1f3fde8 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners
Reference 47
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Observation cad4fde1-361c-49c6-b4aa-03316ac2335f · outbound
Kinetics: Rethinking Test-Time Scaling Laws MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding
Reference 48
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Observation b8e7e5aa-9c34-4451-bf7a-0d520a1403d1 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Reference 49
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Observation 644ba042-e62d-43e8-b36d-cda667cc8f7d · outbound
Kinetics: Rethinking Test-Time Scaling Laws Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Reference 50
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Observation 2122038e-f8b7-4b8f-8ae8-c0b6172ef580 · outbound
Kinetics: Rethinking Test-Time Scaling Laws ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference
Reference 51
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Observation 1f9d6edd-9263-434b-b776-3b3437af8323 · outbound
Kinetics: Rethinking Test-Time Scaling Laws LLM Pretraining with Continuous Concepts
Reference 52
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Observation 8b93b88b-f13c-4dd1-a139-1f5daea7b325 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference
Reference 53
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Observation d6006ae1-8995-429c-99c8-0c3945142982 · outbound
Kinetics: Rethinking Test-Time Scaling Laws M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models
Reference 55
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Observation 7ba3c48d-c8c0-46ff-823f-a30d79e9b952 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models
Reference 56
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Unavailable: canonical work link unavailable.
Observation e73ac66e-3bca-4c1e-aa00-dc59004ac2fe · outbound
Kinetics: Rethinking Test-Time Scaling Laws Efficient Streaming Language Models with Attention Sinks
Reference 57
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Observation b07c3763-8c89-4860-8531-e0bfb19271a4 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Qwen2 Technical Report
Reference 58
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Observation 13e7a974-fe98-4837-832b-e201e5be6bc5 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Qwen3 Technical Report
Reference 59
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Observation 4c04b01e-0c77-456a-bba7-8938d89d8292 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention
Reference 60
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Unavailable: canonical work link unavailable.
Observation dcfdf893-6348-4cbd-95bc-e83b1ef50f6a · outbound
Kinetics: Rethinking Test-Time Scaling Laws LLM Inference Unveiled: Survey and Roofline Model Insights
Reference 61
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Observation 3ed5c8bc-4d41-4e67-944b-094d4c152d89 · outbound
Kinetics: Rethinking Test-Time Scaling Laws OPT: Open Pre-trained Transformer Language Models
Reference 62
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Unavailable: canonical work link unavailable.
Observation 9636216e-aac4-4212-a1ed-e54d8b11d05d · outbound
Kinetics: Rethinking Test-Time Scaling Laws NanoFlow: Towards Optimal Large Language Model Serving Throughput
Reference 63
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Unavailable: canonical work link unavailable.
Observation 144903df-542b-4753-9db1-1e5b0d74243d · outbound
Kinetics: Rethinking Test-Time Scaling Laws For the Qwen3 series, this additional overhead is bounded by 3.57% for the 0.6B model and by 1.56% for the 32B model
Reference 64
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0f312401-9f31-4b72-a821-c92e42ddf92a · outbound
Kinetics: Rethinking Test-Time Scaling Laws LiveCodeBench features complex programming problems from recent coding contests, while AIME25 consists of challenging math problems
Reference 65
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation cfb97397-1dab-46e5-9431-1a22820548a2 · outbound
Kinetics: Rethinking Test-Time Scaling Laws In parallel, approaches like FlashAttention (Dao et al., 2022; Dao,
Reference 66
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f65f81ba-b263-4109-9fa5-77478e6f9397 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Unresolved cited work
Reference 67
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 63f381e5-9da3-44d9-97a1-9ea056c8ae3f · outbound
Kinetics: Rethinking Test-Time Scaling Laws Our analysis builds on the practical designs and implementations of these systems
Reference 68
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 26519990-d61a-47b4-893f-a381711f8071 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Additionally, model compression and offloading (Dettmers et al., 2022; Lin et al., 29 2024a; Svirschevski et al., 2024; Sheng et al., 2023; Frantar et al.,
Reference 69
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 485c0785-0d1c-4cba-bf9b-1950eb07c03e · outbound
Kinetics: Rethinking Test-Time Scaling Laws Unresolved cited work
Reference 70
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6afc88df-97f5-4a9d-bda0-c1a779b24991 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Efficient reward-model-based (Wu et al., 2024; Snell et al., 2024; Sun et al., 2024c) test-time scaling algorithms are also comprehensively studied
Reference 71
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 90dada2a-a842-4645-8862-d9b62d8c81e1 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Nvidia blackwell platform: Advancing generative ai and accelerated computing
Reference 1996
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5c49558e-3fa6-4a63-8b8f-92ce35c12372 · outbound
Kinetics: Rethinking Test-Time Scaling Laws s1: Simple test-time scaling
Reference 2017
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Unavailable: canonical work link unavailable.
Observation 557f2613-81ad-44b6-9090-c975746cc0df · outbound
Kinetics: Rethinking Test-Time Scaling Laws Rethinking Attention with Performers
Reference 2019
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Unavailable: canonical work link unavailable.
Observation 5de5f4a4-4bf0-4e26-9c4d-e303b78c1df2 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
Reference 2020
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Unavailable: canonical work link unavailable.
Observation f8106308-40c9-48c7-ab8e-97516f9a1067 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Accelerating Large Language Model Decoding with Speculative Sampling
Reference 2021
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Unavailable: canonical work link unavailable.
Observation 13201d32-6782-410b-ab1b-7664bb36fd8b · outbound
Kinetics: Rethinking Test-Time Scaling Laws SMYRF: Efficient Attention using Asymmetric Clustering
Reference 2022
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e8e64e95-ca1d-49b7-bed5-f699951ef985 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Reinforcement Learning for Long-Horizon Interactive LLM Agents
Reference 2023
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Unavailable: canonical work link unavailable.
Observation 7a14e433-d084-41a8-b1a7-a3f68645201e · outbound
Kinetics: Rethinking Test-Time Scaling Laws LoCoCo: Dropping In Convolutions for Long Context Compression
Reference 2024
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Unavailable: canonical work link unavailable.
Observation bf7534e3-9452-4d0e-8355-73f3ff28b719 · outbound
Kinetics: Rethinking Test-Time Scaling Laws Daman Arora and Andrea Zanette
Reference 2025
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Unavailable: canonical work link unavailable.
Observation a9623f3c-31bf-46fb-83f7-9e303317fef2 · inbound
Sparrow: Sparse Rollout for Stable and Efficient Long-context RL of Large Language Models Kinetics: Rethinking Test-Time Scaling Laws
Reference 14
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 729314ea-acfa-49bb-bb0f-bc4e55f461f7 · inbound
Interpretable Adaptive Sampling for LLM Test-Time Scaling Kinetics: Rethinking Test-Time Scaling Laws
Reference 16
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Unavailable: canonical work link unavailable.