Cost + Long Horizon Metric Papers

Updated from current HFEPX corpus (Feb 27, 2026). This page tracks 12 papers for Cost + Long Horizon Metric Papers. Dominant protocol signals include automatic metrics, simulation environments, with frequent benchmark focus on ALFWorld, BrowseComp and metric focus on cost, accuracy. Use the grounded sections below to prioritize reproducible protocol choices, benchmark-matched comparisons, and judge-vs-human evaluation checks.

Top Papers Reporting This Metric

• Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching

  Roy Miles, Aysim Toker, Andreea-Maria Oncescu, Songcen Xu, Jiankang Deng · Feb 26, 2026

  Automatic Metrics MathCoding

  This modular pipeline separates exploration (diffusion) from evaluation and solution synthesis, avoiding monolithic unified hybrids while preserving broad search.

• Replacing Multi-Step Assembly of Data Preparation Pipelines with One-Step LLM Pipeline Generation for Table QA

  Fengyu Li, Junhao Zhu, Kaishi Song, Lu Chen, Zhongming Yao · Feb 26, 2026

  Automatic Metrics General

  Experiments on two benchmark datasets show that, with the same LLM backbone, Operation-R1 achieves average absolute accuracy gains of 9.55 and 6.08 percentage points over multi-step preparation baselines, with 79\% table compression and a 2

• Search More, Think Less: Rethinking Long-Horizon Agentic Search for Efficiency and Generalization

  Qianben Chen, Tianrui Qin, King Zhu, Qiexiang Wang, Chengjun Yu · Feb 26, 2026

  Automatic Metrics General

  Recent deep research agents primarily improve performance by scaling reasoning depth, but this leads to high inference cost and latency in search-intensive scenarios.

• How Do Latent Reasoning Methods Perform Under Weak and Strong Supervision?

  Yingqian Cui, Zhenwei Dai, Bing He, Zhan Shi, Hui Liu · Feb 25, 2026

  Automatic Metrics Coding

  Latent reasoning has been recently proposed as a reasoning paradigm and performs multi-step reasoning through generating steps in the latent space instead of the textual space.

• SWE-Protégé: Learning to Selectively Collaborate With an Expert Unlocks Small Language Models as Software Engineering Agents

  Patrick Tser Jern Kon, Archana Pradeep, Ang Chen, Alexander P. Ellis, Warren Hunt · Feb 25, 2026

  Automatic Metrics Coding

  Our approach combines supervised fine-tuning on expert-augmented trajectories with agentic reinforcement learning that explicitly discourages degenerative looping and unproductive expert collaboration.

• Continuous Telemonitoring of Heart Failure using Personalised Speech Dynamics

  Yue Pan, Xingyao Wang, Hanyue Zhang, Liwei Liu, Changxin Li · Feb 23, 2026

  Automatic Metrics MedicineCoding

  The model's high sensitivity was further corroborated by additional follow-up data, confirming its efficacy in predicting HF deterioration and its potential to secure patient safety in remote, home-based settings.

• Do LLMs and VLMs Share Neurons for Inference? Evidence and Mechanisms of Cross-Modal Transfer

  Chenhang Cui, An Zhang, Yuxin Chen, Gelei Deng, Jingnan Zheng · Feb 22, 2026

  Automatic Metrics MathCoding

  Across diverse mathematics and perception benchmarks, SNRF consistently enhances LVLM inference performance while preserving perceptual capabilities.

• Watermarking LLM Agent Trajectories

  Wenlong Meng, Chen Gong, Terry Yue Zhuo, Fan Zhang, Kecen Li · Feb 21, 2026

  Automatic Metrics MathCoding

  LLM agents rely heavily on high-quality trajectory data to guide their problem-solving behaviors, yet producing such data requires substantial task design, high-capacity model generation, and manual filtering.

• Sink-Aware Pruning for Diffusion Language Models

  Aidar Myrzakhan, Tianyi Li, Bowei Guo, Shengkun Tang, Zhiqiang Shen · Feb 19, 2026

  Automatic Metrics Coding

  Diffusion Language Models (DLMs) incur high inference cost due to iterative denoising, motivating efficient pruning.

• TabAgent: A Framework for Replacing Agentic Generative Components with Tabular-Textual Classifiers

  Ido Levy, Eilam Shapira, Yinon Goldshtein, Avi Yaeli, Nir Mashkif · Feb 18, 2026

  Automatic Metrics General

  Agentic systems, AI architectures that autonomously execute multi-step workflows to achieve complex goals, are often built using repeated large language model (LLM) calls for closed-set decision tasks such as routing, shortlisting, gating,

• Embodied Task Planning via Graph-Informed Action Generation with Large Language Model

  Xiang Li, Ning Yan, Masood Mortazavi · Jan 29, 2026

  Simulation Env Coding

  While Large Language Models (LLMs) have demonstrated strong zero-shot reasoning capabilities, their deployment as embodied agents still faces fundamental challenges in long-horizon planning.

• Aerial Vision-Language Navigation with a Unified Framework for Spatial, Temporal and Embodied Reasoning

  Huilin Xu, Zhuoyang Liu, Yixiang Luomei, Feng Xu · Dec 9, 2025

  Simulation Env General

  Extensive experiments on the AerialVLN and OpenFly benchmark validate the effectiveness of our method.

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