A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? | Paper Citation Record

Observation 6ff1a7ce-37e5-466c-9258-0f89657ce664 · inbound

Language Model Networks: Supervision-Efficient Learning through Dense Communication cites this paper.

Language Model Networks: Supervision-Efficient Learning through Dense Communication A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-05-22T14:51:41.922988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 08a67229-bf5c-4b5f-8c83-6836f7d9bf24 · inbound

DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning cites this paper.

DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6ed33c05-2a02-4ce3-aa86-bc2c4b58f7ce · inbound

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence cites this paper.

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 203

Resolution: metadata mismatch; local_arxiv, observed 2026-05-14T22:23:15.079043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 80f230ee-eecb-4e52-b148-cd867b81ab4a · inbound

An Auditable Agent Platform For Automated Molecular Optimisation cites this paper.

An Auditable Agent Platform For Automated Molecular Optimisation A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T04:32:28.414316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dd8f729-a7c6-45d6-8cbb-6940b1fb8c1c · inbound

ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments cites this paper.

ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-19T01:02:54.846516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0c4e2cd7-5941-4339-97ab-2d00cbb92056 · inbound

Keyword-Centric Prompting for One-Shot Event Detection with Self-Generated Rationale Enhancements cites this paper.

Keyword-Centric Prompting for One-Shot Event Detection with Self-Generated Rationale Enhancements A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T22:05:41.175894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aec27a67-80b0-4012-962a-548a8eece983 · inbound

Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization cites this paper.

Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:31:53.158218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 635baa46-0aa2-4c0c-83e7-d034e1aa98a7 · inbound

Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models cites this paper.

Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T20:21:08.251549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54282c77-7e8e-4286-a164-1fef4fd1a4b1 · inbound

A Lightweight Incentive-Based Privacy-Preserving Smart Metering Protocol for Value-Added Services cites this paper.

A Lightweight Incentive-Based Privacy-Preserving Smart Metering Protocol for Value-Added Services A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T18:22:38.859325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 361b3c4b-d395-48b3-845d-fe628de702e8 · inbound

Thinking Before You Speak: A Proactive Test-time Scaling Approach cites this paper.

Thinking Before You Speak: A Proactive Test-time Scaling Approach A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T16:23:38.548888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be4774e0-2ba7-44fc-8c21-b3f7d2849f9d · inbound

Learning to Refine: Self-Refinement of Parallel Reasoning in LLMs cites this paper.

Learning to Refine: Self-Refinement of Parallel Reasoning in LLMs A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-05-18T21:16:51.034192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bea2c57e-65ec-41ae-8802-3c9f90c5d6b3 · inbound

Implicit Reasoning in Large Language Models: A Comprehensive Survey cites this paper.

Implicit Reasoning in Large Language Models: A Comprehensive Survey A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-05T11:39:36.836416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ff7f1ea-4082-41c1-90fb-2770e16904bf · inbound

Scaling Up, Speeding Up: A Benchmark of Speculative Decoding for Efficient LLM Test-Time Scaling cites this paper.

Scaling Up, Speeding Up: A Benchmark of Speculative Decoding for Efficient LLM Test-Time Scaling A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T13:48:23.144764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ca57269-32e3-4cf5-81e8-218e9eb3b865 · inbound

Hunyuan-MT Technical Report cites this paper.

Hunyuan-MT Technical Report A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-05T05:33:35.588351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7169412-fd5a-4bec-adf4-814bad7d7b24 · inbound

Staying in the Sweet Spot: Responsive Reasoning Evolution via Capability-Adaptive Hint Scaffolding cites this paper.

Staying in the Sweet Spot: Responsive Reasoning Evolution via Capability-Adaptive Hint Scaffolding A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T22:57:45.084185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06d80029-523d-43c1-af6e-a4aad1154b4a · inbound

Ubiquitous Intelligence Via Wireless Network-Driven LLMs Evolution cites this paper.

Ubiquitous Intelligence Via Wireless Network-Driven LLMs Evolution A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T20:42:45.659388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ff00574-128a-4c4e-aa0f-46bfa8cce16f · inbound

Thinking Sparks!: Emergent Attention Heads in Reasoning Models During Post Training cites this paper.

Thinking Sparks!: Emergent Attention Heads in Reasoning Models During Post Training A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 55

Resolution: verified exact; local_arxiv, observed 2026-05-18T13:31:25.018073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 92a13153-073c-4d94-bbe3-e1ab20c9601d · inbound

RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling cites this paper.

RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-18T05:15:54.301956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 24916366-268e-456d-9014-404a81e39914 · inbound

Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment cites this paper.

Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-05-16T12:27:52.321859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1d2d0a93-473d-447a-b361-53515bf69383 · inbound

Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment cites this paper.

Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T09:22:48.116395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74e38ed2-f0ba-45a3-b40e-388c51b635e6 · inbound

ETS: Energy-Guided Test-Time Scaling for Training-Free RL Alignment cites this paper.

ETS: Energy-Guided Test-Time Scaling for Training-Free RL Alignment A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-05-16T09:40:49.055978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6d2fbad8-8e70-43d4-b9e2-5c2df885c689 · inbound

ETS: Energy-Guided Test-Time Scaling for Training-Free RL Alignment cites this paper.

ETS: Energy-Guided Test-Time Scaling for Training-Free RL Alignment A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-05-21T14:10:13.491193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 215eb138-c5f2-4e2a-91f3-5be6a610ed3e · inbound

CODA: Difficulty-Aware Compute Allocation for Adaptive Reasoning cites this paper.

CODA: Difficulty-Aware Compute Allocation for Adaptive Reasoning A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-05-15T14:25:55.496930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5c9825f0-a7a8-4545-b0e5-e93100d8a2a9 · inbound

EndoCoT: Scaling Endogenous Chain-of-Thought Reasoning in Diffusion Models cites this paper.

EndoCoT: Scaling Endogenous Chain-of-Thought Reasoning in Diffusion Models A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-14T22:25:04.080629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db38a336-7c6f-45b1-94e2-630e94abc879 · inbound

Superbunched random fiber laser cites this paper.

Superbunched random fiber laser A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 62

Resolution: unresolved; no resolver link, observed 2026-07-13T20:31:07.902275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29c3760e-7599-49a9-b847-138b70b74f46 · inbound

From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning cites this paper.

From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f2cf3053-f596-43c0-bcb9-400a852fa259 · inbound

AdverMCTS: Combating Pseudo-Correctness in Code Generation via Adversarial Monte Carlo Tree Search cites this paper.

AdverMCTS: Combating Pseudo-Correctness in Code Generation via Adversarial Monte Carlo Tree Search A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1202bc53-24f8-4823-97bf-cd004b5bcb83 · inbound

Test-time Scaling over Perception: Resolving the Grounding Paradox in Thinking with Images cites this paper.

Test-time Scaling over Perception: Resolving the Grounding Paradox in Thinking with Images A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a05c182a-3b90-4dc6-be36-131d3b225e1a · inbound

Test-time Scaling over Perception: Resolving the Grounding Paradox in Thinking with Images cites this paper.

Test-time Scaling over Perception: Resolving the Grounding Paradox in Thinking with Images A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T05:31:43.668949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45020902-06d3-4d75-8989-46652412f6b0 · inbound

Training-Free Test-Time Contrastive Learning for Large Language Models cites this paper.

Training-Free Test-Time Contrastive Learning for Large Language Models A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9c331f8e-3d56-428e-99a8-1c05e5d0b725 · inbound

MARS$^2$: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation cites this paper.

MARS$^2$: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f85c44c7-9e02-4dc4-bacd-330e4c8661cb · inbound

Adaptive Test-Time Compute Allocation for Reasoning LLMs via Constrained Policy Optimization cites this paper.

Adaptive Test-Time Compute Allocation for Reasoning LLMs via Constrained Policy Optimization A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f38c4e9e-bd5d-4679-a284-a33a0b9a2e63 · inbound

Clover: A Neural-Symbolic Agentic Harness with Stochastic Tree-of-Thoughts for Verified RTL Repair cites this paper.

Clover: A Neural-Symbolic Agentic Harness with Stochastic Tree-of-Thoughts for Verified RTL Repair A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f8acaef1-d0f7-43c8-8a76-aa0792dea3ea · inbound

Hive: A Multi-Agent Infrastructure for Algorithm- and Task-Level Scaling cites this paper.

Hive: A Multi-Agent Infrastructure for Algorithm- and Task-Level Scaling A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 87813a6b-98f4-4a28-90b7-ed375d9be44f · inbound

ComPASS: Towards Personalized Agentic Social Support via Tool-Augmented Companionship cites this paper.

ComPASS: Towards Personalized Agentic Social Support via Tool-Augmented Companionship A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a8f18fe7-165c-4319-803b-cdbef7de8cda · inbound

Evaluation-driven Scaling for Scientific Discovery cites this paper.

Evaluation-driven Scaling for Scientific Discovery A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 172

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 41daeef1-84a9-473a-9e10-044d5fbfcba4 · inbound

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling cites this paper.

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7c1b6035-7cef-45f8-ba83-0abc668be8af · inbound

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling cites this paper.

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T05:23:31.417314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 040c9a7c-1c1a-4ddd-8a7a-fc16efeb42c6 · inbound

VLA-ATTC: Adaptive Test-Time Compute for VLA Models with Relative Action Critic Model cites this paper.

VLA-ATTC: Adaptive Test-Time Compute for VLA Models with Relative Action Critic Model A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cf2b85a0-724e-4107-90b1-9350996c6eb3 · inbound

Stream-T1: Test-Time Scaling for Streaming Video Generation cites this paper.

Stream-T1: Test-Time Scaling for Streaming Video Generation A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e3a48133-6027-4db9-a8af-e7fb77f0be0d · inbound

BitCal-TTS: Bit-Calibrated Test-Time Scaling for Quantized Reasoning Models cites this paper.

BitCal-TTS: Bit-Calibrated Test-Time Scaling for Quantized Reasoning Models A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 168deb9b-cf9c-4a71-ae76-698f0a7ce50a · inbound

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents cites this paper.

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 960fc558-7a55-4856-81c2-301c403ec0f8 · inbound

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents cites this paper.

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 695fbc2a-66c9-4b7c-b205-58776af2508d · inbound

CA-SQL: Complexity-Aware Inference Time Reasoning for Text-to-SQL via Exploration and Compute Budget Allocation cites this paper.

CA-SQL: Complexity-Aware Inference Time Reasoning for Text-to-SQL via Exploration and Compute Budget Allocation A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b09f5760-0e30-4caf-a90f-3e35295e1a32 · inbound

Forge: Quality-Aware Reinforcement Learning for NP-Hard Optimization in LLMs cites this paper.

Forge: Quality-Aware Reinforcement Learning for NP-Hard Optimization in LLMs A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e59d44d9-d712-45d1-b0f2-23acfeac2dd8 · inbound

The Agent Use of Agent Beings: Agent Cybernetics Is the Missing Science of Foundation Agents cites this paper.

The Agent Use of Agent Beings: Agent Cybernetics Is the Missing Science of Foundation Agents A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1e831801-3de3-41b3-9d8a-9af4231f8f9e · inbound

Nice Fold or Hero Call: Learning Budget-Efficient Thinking for Adaptive Reasoning cites this paper.

Nice Fold or Hero Call: Learning Budget-Efficient Thinking for Adaptive Reasoning A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ae42288a-9be8-46e5-8e30-a62525f85f66 · inbound

HSUGA: LLM-Enhanced Recommendation with Hierarchical Semantic Understanding and Group-Aware Alignment cites this paper.

HSUGA: LLM-Enhanced Recommendation with Hierarchical Semantic Understanding and Group-Aware Alignment A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:07:52.994249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1b6aa264-76fe-4380-a872-7747055fc08c · inbound

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos cites this paper.

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-20T10:58:13.827505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8c48f4fd-a5ee-484b-abcf-b08f38131768 · inbound

TapSampling: Inference-Time Sampling with a Task-Progress-Understanding Verifier for Robotic Manipulation cites this paper.

TapSampling: Inference-Time Sampling with a Task-Progress-Understanding Verifier for Robotic Manipulation A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-06-29T22:04:00.515048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 42aadb2a-f61b-467d-83a3-c564be5b5066 · inbound

Share More, Search Less: Collaborative Parallel Thinking for Efficient Test-Time Scaling cites this paper.

Share More, Search Less: Collaborative Parallel Thinking for Efficient Test-Time Scaling A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-06-29T18:33:51.112926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 562a2218-671f-4753-b1d0-037a9886f0c1 · inbound

Can Hallucinations Be Useful? Solving Multi-Hop Questions With SLMs By Chaining System-I/II Reasoning cites this paper.

Can Hallucinations Be Useful? Solving Multi-Hop Questions With SLMs By Chaining System-I/II Reasoning A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-06-29T18:33:50.714947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 363cea04-bcd0-4043-8fd0-5b573bb6671c · inbound

What Am I Missing? Question-Answering as Hidden State Probing cites this paper.

What Am I Missing? Question-Answering as Hidden State Probing A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-07-01T19:36:08.896349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4a9f7ac8-43c2-4712-adea-32e542c791e9 · inbound

Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling cites this paper.

Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 95

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T02:56:30.014006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 03ae8aef-6ce3-4e79-83fb-803d3940b818 · inbound

EASE-TTT: Evidence-Aligned Selective Test-Time Training for Long-Context Question Answering cites this paper.

EASE-TTT: Evidence-Aligned Selective Test-Time Training for Long-Context Question Answering A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T17:17:15.117878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7945aff2-afa2-4cab-b463-51f8cc0679e0 · inbound

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning cites this paper.

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 111

Resolution: verified exact; local_arxiv, observed 2026-07-02T21:37:25.411539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cf5cc54c-97e8-46c7-b011-7809185b3168 · inbound

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI cites this paper.

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 160

Resolution: unresolved; no resolver link, observed 2026-08-02T11:29:33.291784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8eb7da15-fae3-4903-99e1-a21da45fda28 · inbound

Dynamic Rollout Editing for Reducing Overthinking in RL-Trained Reasoning Models cites this paper.

Dynamic Rollout Editing for Reducing Overthinking in RL-Trained Reasoning Models A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-06-27T01:20:20.424956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 588eb31e-9163-441f-aef9-3c09c37190df · inbound

When More Sampling Hurts: The Modal Ceiling and Correlation Ceiling of Test-Time Scaling cites this paper.

When More Sampling Hurts: The Modal Ceiling and Correlation Ceiling of Test-Time Scaling A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-06-30T09:44:37.108721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f80e9360-d2ea-45da-8a55-ed340935577f · inbound

DriveVer: Lightweight Trajectory Evaluator as Test-Time Verifier for Autonomous Driving cites this paper.

DriveVer: Lightweight Trajectory Evaluator as Test-Time Verifier for Autonomous Driving A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-02T15:07:04.062390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c3f52520-79bc-49b9-9ab5-59ebf80e1509 · inbound

Precise but Uncoupled: Reviewer Precision Does Not Guarantee Critique Uptake in Multi-Agent Math Reasoning cites this paper.

Precise but Uncoupled: Reviewer Precision Does Not Guarantee Critique Uptake in Multi-Agent Math Reasoning A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T23:34:09.881076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6412470-d92e-45ab-876d-198c85f41806 · inbound

Fishing Out Free Riders: Shapley-Based Reward Attribution for Parallel Reasoning via Reinforcement Learning cites this paper.

Fishing Out Free Riders: Shapley-Based Reward Attribution for Parallel Reasoning via Reinforcement Learning A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T13:54:18.292672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2543b24-09ef-4288-bffd-db2be8b8fe91 · inbound

Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning cites this paper.

Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 1989

Resolution: unresolved; no resolver link, observed 2026-08-01T06:17:30.106561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b21b7678-ebc5-4a4b-b23a-6559ed780ed6 · inbound

SpecCal: Ambiguity-Aware Candidate Calibration for Infrared Spectrum-Based Molecular Structure Reconstruction cites this paper.

SpecCal: Ambiguity-Aware Candidate Calibration for Infrared Spectrum-Based Molecular Structure Reconstruction A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-01T01:25:07.947759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bff5347-115f-47a1-be8d-4f4b0d0e1253 · inbound

Cognitive Demand Steering for Adaptive Meta-Reasoning in Large Language Models cites this paper.

Cognitive Demand Steering for Adaptive Meta-Reasoning in Large Language Models A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T00:24:22.524838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f257e14-f413-474f-975e-6fdf0caf3909 · inbound

Test-Time Scalable AI-RAN: Inference Time Allocation for Cell-Free MIMO cites this paper.

Test-Time Scalable AI-RAN: Inference Time Allocation for Cell-Free MIMO A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T16:03:54.903882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f76510a-7edb-4cfd-ba98-a124dbe8e1be · inbound

Interpretable Adaptive Sampling for LLM Test-Time Scaling cites this paper.

Interpretable Adaptive Sampling for LLM Test-Time Scaling A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T05:02:10.759585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers