Throughput Metric Papers

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• Self-Correcting VLA: Online Action Refinement via Sparse World Imagination

  Chenyv Liu, Wentao Tan, Lei Zhu, Fengling Li, Jingjing Li · Feb 25, 2026

  Simulation Env Coding

  Reinforcement learning enhances physical grounding through exploration yet typically relies on external reward signals that remain isolated from the agent's internal states.

• The Headless Firm: How AI Reshapes Enterprise Boundaries

  Tassilo Klein, Sebastian Wieczorek · Feb 24, 2026

  Automatic Metrics General

  We argue that agentic AI induces a structural change in how coordination costs scale: in prior modular systems, integration cost grew with interaction topology (O(n^2) in the number of components); in protocol-mediated agentic systems, inte

• Towards single-shot coherent imaging via overlap-free ptychography

  Oliver Hoidn, Aashwin Mishra, Steven Henke, Albert Vong, Matthew Seaberg · Feb 24, 2026

  Automatic Metrics General

  On synthetic benchmarks, reconstructions remain accurate at low counts ($\sim\!10^4$ photons/frame), and overlap-free single-shot reconstruction with an experimental probe reaches amplitude structural similarity (SSIM) 0.904, compared with

• CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference

  Chao Fei, Guozhong Li, Chenxi Liu, Panos Kalnis · Feb 24, 2026

  Automatic Metrics Coding

  Extensive evaluations demonstrate that CHESS surpasses Full-KV quality using only \textbf{1\%} of the KV cache, delivers low-latency stable inference with up to \textbf{4.56$\times$} higher throughput, and consistently outperforms other str

• Natural Language Processing Models for Robust Document Categorization

  Radoslaw Roszczyk, Pawel Tecza, Maciej Stodolski, Krzysztof Siwek · Feb 23, 2026

  Automatic Metrics General

  This article presents an evaluation of several machine learning methods applied to automated text classification, alongside the design of a demonstrative system for unbalanced document categorization and distribution.

• Anatomy of Agentic Memory: Taxonomy and Empirical Analysis of Evaluation and System Limitations

  Dongming Jiang, Yi Li, Songtao Wei, Jinxin Yang, Ayushi Kishore · Feb 22, 2026

  Automatic Metrics General

  Agentic memory systems enable large language model (LLM) agents to maintain state across long interactions, supporting long-horizon reasoning and personalization beyond fixed context windows.

• Luna-2: Scalable Single-Token Evaluation with Small Language Models

  Vatsal Goel, Rishon Dsouza, Nikhil Ega, Amey Ramesh Rambatla, Rob Friel · Feb 20, 2026

  Automatic Metrics Coding

  Real-time guardrails require evaluation that is accurate, cheap, and fast - yet today's default, LLM-as-a-judge (LLMAJ), is slow, expensive, and operationally non-deterministic due to multi-token generation.

• SPQ: An Ensemble Technique for Large Language Model Compression

  Jiamin Yao, Eren Gultepe · Feb 20, 2026

  Automatic MetricsSimulation Env MathCoding

  Applied to LLaMA-2-7B, SPQ achieves up to 75% memory reduction while maintaining or improving perplexity (e.g., WikiText-2 5.47 to 4.91) and preserving accuracy on downstream benchmarks such as C4, TruthfulQA, and GSM8K.

• AI-Driven Structure Refinement of X-ray Diffraction

  Bin Cao, Qian Zhang, Zhenjie Feng, Taolue Zhang, Jiaqiang Huang · Feb 18, 2026

  Automatic Metrics Law

  We benchmark WPEM on standard reference patterns (PbSO$_4$ and Tb$_2$BaCoO$_5$), where it yields lower $R_p/R_{wp}$ than widely used packages (FullProf and TOPAS) under matched refinement conditions.

• PREFER: An Ontology for the PREcision FERmentation Community

  Txell Amigó, Shawn Zheng Kai Tan, Angel Luu Phanthanourak, Sebastian Schulz, Pasquale D. Colaianni · Feb 18, 2026

  Automatic Metrics General

  Precision fermentation relies on microbial cell factories to produce sustainable food, pharmaceuticals, chemicals, and biofuels.

• CryoLVM: Self-supervised Learning from Cryo-EM Density Maps with Large Vision Models

  Weining Fu, Kai Shu, Kui Xu, Qiangfeng Cliff Zhang · Feb 2, 2026

  Automatic Metrics General

  Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by enabling near-atomic-level visualization of biomolecular assemblies.

• Towards Efficient Agents: A Co-Design of Inference Architecture and System

  Weizhe Lin, Hui-Ling Zhen, Shuai Yang, Xian Wang, Renxi Liu · Dec 20, 2025

  Automatic Metrics General

  The rapid development of large language model (LLM)-based agents has unlocked new possibilities for autonomous multi-turn reasoning and tool-augmented decision-making.

• Batch Prompting Suppresses Overthinking Reasoning Under Constraint: How Batch Prompting Suppresses Overthinking in Reasoning Models

  Saurabh Srivastava, Janit Bidhan, Hao Yan, Abhishek Dey, Tanu Kansal · Nov 6, 2025

  Automatic Metrics General

  Across 13 diverse benchmarks with DeepSeek-R1 and OpenAI-o1, batch prompting {reduces reasoning tokens by 76\% (2{,}950$\mapsto$710), on average, while preserving or improving accuracy}.

• ATTS: Asynchronous Test-Time Scaling via Conformal Prediction

  Jing Xiong, Qiujiang Chen, Fanghua Ye, Zhongwei Wan, Chuanyang Zheng · Sep 18, 2025

  Automatic Metrics MathCoding

  Large language models (LLMs) benefit from test-time scaling but are often hampered by high inference latency.

• Semantic Parallelism: Redefining Efficient MoE Inference via Model-Data Co-Scheduling

  Yan Li, Zhenyu Zhang, Zhengang Wang, Pengfei Chen, Pengfei Zheng · Mar 6, 2025

  Automatic Metrics General

  Prevailing LLM serving engines employ expert parallelism (EP) to implement multi-device inference of massive MoE models.

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