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arXivTest-time compute

Towards In-Parameter Memory Augmentation for Large Language Models

This survey organizes in-parameter memory augmentation for LLMs by parameter placement and acquisition time to enable reusable parametric knowledge at deployment.

Haoyu Huang, Zhongwei Xie, Jiaxin Bai, Yisen Gao and 5 more

Published Oct 6, 2026 · ▲ 5 on Hugging Face · Code ★ 1

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arXivTest-time compute

Self-Generated Feedback Destabilizes Test-Time Training: A Causal Decomposition of Long-Horizon Adaptation

Self-generated feedback in long-horizon test-time training causes weight updates that improve synthetic text but degrade real-text prediction, and settlement on independent evidence prevents this failure.

Cheng Luo, Bing Li, Bernard Ghanem

Published Oct 4, 2026 · ▲ 19 on Hugging Face · Code ★ 1

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arXivTest-time compute

ALoDLM: Adaptively Looped Diffusion Language Models

ALoDLM applies token-adaptive latent recurrence to diffusion language models, allocating computation by difficulty to close the quality gap with autoregressive models at 1.7B and 8B scales.

Liancheng Fang, Zhuowei Li, Youngeun Kim, Tianchen Zhao and 9 more

Published Oct 3, 2026 · ▲ 55 on Hugging Face · Code ★ 4

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arXivTest-time compute

ReSolve: Reusing Candidate Reasoning through Selective Generative Moderation

ReSolve reuses candidate reasoning via selective generative moderation to boost math accuracy and cut token use versus voting and self-consistency.

Bangji Yang, Jiajun Fan, MA Hongba, Xi Zhu and 5 more

Published Oct 1, 2026 · 0 citations

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arXivTest-time compute

Learning to Predict Distributions over Weight Updates for Test-Time Adaptation

Query-conditioned hypernetworks predict distributions over LoRA weight updates from input queries, enabling test-time scaling via sampled adapted models that outperform deterministic and token-sampling baselines.

Azal Ahmad Khan, Keshav Ramji, Tahira Naseem, Ali Anwar and 1 more

Published Oct 1, 2026 · 0 citations

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arXivGoogleTest-time compute

LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling

AutoTTS automatically discovers test-time scaling strategies via environment-driven controller synthesis, improving LLM reasoning accuracy-cost tradeoffs over manual baselines at minimal cost.

Tong Zheng, Haolin Liu, Chengsong Huang, Huiwen Bao and 9 more

Published May 8, 2026 · 0 citations · ▲ 70 on Hugging Face · Code ★ 176

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arXivTest-time compute

TTCS: Test-Time Curriculum Synthesis for Self-Evolving

TTCS uses a co-evolving question synthesizer and reasoning solver to build test-time curricula that stabilize self-updates and improve reasoning on hard math benchmarks.

Chengyi Yang, Zhiyi Xiang, Yunbo Tang, Zongpei Teng and 4 more

Published Jan 30, 2026 · 0 citations · ▲ 35 on Hugging Face · Code ★ 53

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ACL 2026U WashingtonNew YorkMassachusetts Institute of TechnStanfordTest-time compute

When One LLM Drools, Multi-LLM Collaboration Rules

Multi-LLM collaboration outperforms single LLM reasoning on tasks where individual models fail, demonstrating collective rule over solo drooling.

Shangbin Feng, Wenxuan Ding, Alisa Liu, Zifeng Wang and 9 more

Published 2026 · 1 citation

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arXivTest-time compute

Efficient Test-Time Scaling via Self-Calibration

Self-Calibration distills self-consistency confidence into LLMs for reliable single-pass estimation, enabling confidence-based early stopping that improves MathQA accuracy to 83.6 with 16 samples.

Chengsong Huang, Langlin Huang, Leng, Jixuan, Jiacheng Liu and 1 more

Published Feb 25, 2025 · 1 citation · ▲ 15 on Hugging Face · Code ★ 22

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NeurIPS 2026Tel AvivTechnionMentee RoboticsTest-time compute

Mean-Field Parallel Decoding for Discrete Diffusion Language Models

Tamim Zoabi, Ameen A Ali, Liran Ringel, Lior Wolf

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Google DeepMind, Gatsby UCLU ColoradoGoogle DeepMindGoogleTest-time compute

Catch Your Breath: Adaptive Computation for Self-Paced Sequence Production

Alexandre Galashov, Matt Jones, Nan Rosemary Ke, Yuan Cao and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026MITMassachusetts Institute of TechnTest-time compute

Early Signals, Strong Decisions: Prefix-Guided Sampling for Parallel Test-Time Scaling

Jie Ren, Jonathan S Rosenfeld, Neil Thompson

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026U California, RiversideIndianaTest-time compute

Test-time Scaling for Diffusion Language Models with Frequency-Aware Remasking

Bowen Zuo, Yue Yu, Dongruo Zhou, Yinglun Zhu

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Northwestern PolytechnicalNorthwest Polytechnical UniversiTest-time compute

Relaxation-Aligned State Control for Test-Time Scaling in Generative Combinatorial Optimization

Bohao Li, Ying Li, Pei He, Yangming Guo

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026National University of SingaporeTest-time compute

Confidence-Calibrated Inference Expansion for Evaluator-Guided Test-Time Reasoning

Weida Liang, Kenji Kawaguchi

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ETH Zurich / Max Planck InstitutCornellMcGillETH ZürichTest-time compute

A Model of Diverse Sampling from Language Models

Manuel Prada-Corral, Yahya Emara, Timothy O'Donnell, Ryan Cotterell and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Bangladesh Sweden Polytechnic InTest-time compute

Training Quality Determines Efficiency Boundaries in Test-Time Reasoning

MD Azizul Hakim

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Science and Technology BeijingU New South WalesHarbin Institute of TechnologyUniversity Of New South WalesMacquarieTest-time compute

Test-Time Prompt-Agnostic Decomposition

Junze Wang, Lei Fan, Dezheng Zhang, Donglin Di and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Shanghai Jiao TongWuhanTest-time compute

When Does Structure Help? Statistical Tradeoffs for Structured Reverse Processes in Diffusion Large Language Models

Ruofeng Yang, Jingyuan Liu, Shuai Li

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U North Carolina at Chapel HillNational University of SingaporeU California, Santa BarbaraHarvard University, HarvardNanyang TechnologicalTest-time compute

Denoising Time Matters: Diverse Generation in Diffusion Language Models

jingxuan wu, Zhenglin Wan, Yuzhe YANG, Yiqiao Huang and 4 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026U Science and Technology of ChinU HoustonPayPal Inc.Kent StateTest-time compute

Specialists Hold, Generalists Discount: Asymmetric Equilibrium in LLM Routing Auctions

Xinyu Hou, Yang Lu, Rabimba Karanjai, Pei-Chi Pan and 3 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026NanjingHong Kong University of Science Test-time compute

When LLM Routers Overpay: Strong-Model Over-Selection under Loose Budgets

Guannan Lai, Long Chen, Han-Jia Ye

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026King's College London, UnivKings' College LondonAstraZenecaAstrazenecaThe Chinese University of Hong KTest-time compute

Latent Refinement Decoding: Enhancing Diffusion Language Models by Refining Belief States

Qinglin Zhu, Yizhen Yao, Runcong Zhao, Yanzheng Xiang and 7 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Beijing NormalTest-time compute

Prefill-Guided Trace Allocation for Sample-Efficient Test-Time Scaling

Zhi Yao, Zhiqing Tang, Hanshuai Cui, Qianli Ma and 2 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U TorontoU Hong KongTest-time compute

What should post-training optimize? A test-time scaling law perspective

Muheng Li, Jian Qian, Wenlong Mou

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026JilinInner MongoliaMBZUAI/Jilin U.Test-time compute

Achieve Latency-Efficient Temporal-Coding Spiking LLMs via Discretization-Aware Conversion

Jinjie Fang, Tianxing Man, Xiao Du, Chengxun Jin and 3 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Department of Computer Science aQwen Team & Chinese UniversiU WashingtonChinese University of Hong KongTest-time compute

HiLoRA: Adaptive Hierarchical LoRA Routing for Training-Free Domain Generalization

Ziyi Han, Huanyu Wang, Zeyu Zhang, Xiangxiang Dai and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ConcordiaU Western OntarioSamsungTest-time compute

LLM Routing Through the Lens of Recommendation: A Roadmap for Efficient AI Orchestration

Yuchen Zhou, Boyu Wang, Di Wu

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Institute of Computing TechnologU the Chinese Academy of ScienceU Chinese Academy of SciencesVIPL,ICT,Chinese academic of sciTest-time compute

Geometric Prompt-Trajectory Planning for Test-Time Scaling

Zhengqi Pei, Anran Zhang, Qingming Huang, Shuhui Wang

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Indian Institute of Technology, DeepMindIIT DelhiTest-time compute

Ballad: Bandit-Based LLM Routing for Automated Heuristic Discovery

Samidha Verma, Ankit Anand, Sayan Ranu

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U California San DiegoUC San Diego, Together AIUCSDTest-time compute

Gumbo: Gumbel Optimized High-Temperature Speculative Sampling

Jonah Yi, Dan Fu, Yu-Xiang Wang

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026NankaiThe Hong Kong University of ScieHKUSTZhejiangHong Kong University of Science Test-time compute

SIGMA: A Sigmoid-Gated Sampler for Test-Time Scaling in Diffusion Language Models

Ziwen Zhang, Weiyu Chen, Yuyan Zhou, Yichen Zhu and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Illinois at Urbana ChampaignU Illinois Champaign-UrbanaStanfordU Illinois at Urbana-ChampaignU Illinois Urbana ChampaignTest-time compute

Training Agent to Scale Inference-Time Reasoning

Yunzhe Qi, Sirui Chen, Jiaru Zou, Yanjun Zhao and 2 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Sorbonne UniversitéTest-time compute

Exact Regular-Constrained Sampling for Variable-Order Markov Generation

Francois Pachet

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Hong Kong BaptistBeijing NormalInstitute of automation, ChineseStevens Institute of TechnologyCity University of Hong KongTest-time compute

Not All Low-Confidence Tokens Are Equal: Calibrated Confidence for Efficient Test-Time Reasoning

Tangyu Jiang, Haodi Wang, Yuanbing Zhu, Xiaojiang Du and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026North Carolina StateAssistant Professor, North CarolTest-time compute

StepBack: Step-Level Error-Localized Resampling for Efficient Test-Time Reasoning

Yang Ouyang, Jung-Eun Kim

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026StanfordTest-time compute

Selected-Tail Reliability in Verifier-Guided Best-of-$N$ Inference

Teresa Zhang

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026NorthwesternGE AerospacefalSchool of Computer Science, UnivTest-time compute

Attention Drift: What Auto-Regressive Speculative Decoding Models Learn

Doğaç Eldenk, Payal Mohapatra, Yigitcan Comlek, Kaan Oktay and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Southern CaliforniaToyota Technological Institute aTest-time compute

Adaptive Generate-Rank-Verify: Inference-Time Search with Costly Verification

ADAP adaptively increases response sampling and verification to find verified positives with near-optimal expected cost under monotonic rewards.

Shaddin Dughmi, Mahdi Haghifam, Yusuf H Kalayci

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face · Code ★ 2

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