- SELAUR: Self Evolving LLM Agent via Uncertainty-aware Rewards
Dengjia Zhang, Xiaoou Liu, Lu Cheng, Yaqing Wang, Kenton Murray · Feb 24, 2026 · Citations: 0
Simulation Env Long Horizon
Large language models (LLMs) are increasingly deployed as multi-step decision-making agents, where effective reward design is essential for guiding learning.
- Mobile-Agent-v3.5: Multi-platform Fundamental GUI Agents
Haiyang Xu, Xi Zhang, Haowei Liu, Junyang Wang, Zhaozai Zhu · Feb 15, 2026 · Citations: 0
Simulation Env Long Horizon
The paper introduces GUI-Owl-1.5, the latest native GUI agent model that features instruct/thinking variants in multiple sizes (2B/4B/8B/32B/235B) and supports a range of platforms (desktop, mobile, browser, and more) to enable cloud-edge…
- PMG: Parameterized Motion Generator for Human-like Locomotion Control
Chenxi Han, Yuheng Min, Zihao Huang, Ao Hong, Hang Liu · Feb 13, 2026 · Citations: 0
Automatic Metrics Long Horizon
Recent advances in data-driven reinforcement learning and motion tracking have substantially improved humanoid locomotion, yet critical practical challenges remain.
- AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications
Yujie Zhao, Boqin Yuan, Junbo Huang, Haocheng Yuan, Zhongming Yu · Feb 26, 2026 · Citations: 0
Automatic Metrics Long Horizon
To bridge this gap, we introduce AMA-Bench (Agent Memory with Any length), which evaluates long-horizon memory for LLMs in real agentic applications.
- D-COT: Disciplined Chain-of-Thought Learning for Efficient Reasoning in Small Language Models
Shunsuke Ubukata · Feb 25, 2026 · Citations: 0
Automatic Metrics Long Horizon
In this study, we propose Disciplined Chain-of-Thought (D-CoT), a novel framework that enforces a structured reasoning process using control tags -- such as <TEMP_LOW> for fact-checking and <TEMP_HIGH> for multi-perspective exploration --…
- ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning
Xiaoxuan Wang, Han Zhang, Haixin Wang, Yidan Shi, Ruoyan Li · Feb 25, 2026 · Citations: 0
Simulation Env Long Horizon
Agentic reinforcement learning (ARL) has rapidly gained attention as a promising paradigm for training agents to solve complex, multi-step interactive tasks.
- Learning to Reason for Multi-Step Retrieval of Personal Context in Personalized Question Answering
Maryam Amirizaniani, Alireza Salemi, Hamed Zamani · Feb 22, 2026 · Citations: 0
Pairwise Preference Long Horizon
Personalization in Question Answering (QA) requires answers that are both accurate and aligned with users' background, preferences, and historical context.
- LiLo-VLA: Compositional Long-Horizon Manipulation via Linked Object-Centric Policies
Yue Yang, Shuo Cheng, Yu Fang, Homanga Bharadhwaj, Mingyu Ding · Feb 25, 2026 · Citations: 0
Simulation Env Long Horizon
We introduce a 21-task simulation benchmark consisting of two challenging suites: LIBERO-Long++ and Ultra-Long.
- Hierarchical Reward Design from Language: Enhancing Alignment of Agent Behavior with Human Specifications
Zhiqin Qian, Ryan Diaz, Sangwon Seo, Vaibhav Unhelkar · Feb 20, 2026 · Citations: 0
Pairwise Preference Long Horizon
When training artificial intelligence (AI) to perform tasks, humans often care not only about whether a task is completed but also how it is performed.
- 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 · Citations: 0
Automatic Metrics Long Horizon
Recent deep research agents primarily improve performance by scaling reasoning depth, but this leads to high inference cost and latency in search-intensive scenarios.
- Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids
Victor Reijgwart, Cesar Cadena, Roland Siegwart, Lionel Ott · Feb 24, 2026 · Citations: 0
Simulation Env Long Horizon
Hierarchical, multi-resolution volumetric mapping approaches are widely used to represent large and complex environments as they can efficiently capture their occupancy and connectivity information.
- Beyond Words: Evaluating and Bridging Epistemic Divergence in User-Agent Interaction via Theory of Mind
Minyuan Ruan, Ziyue Wang, Kaiming Liu, Yunghwei Lai, Peng Li · Feb 14, 2026 · Citations: 0
Automatic Metrics Long Horizon
Large Language Models (LLMs) have developed rapidly and are widely applied to both general-purpose and professional tasks to assist human users.
- ICON: Indirect Prompt Injection Defense for Agents based on Inference-Time Correction
Che Wang, Fuyao Zhang, Jiaming Zhang, Ziqi Zhang, Yinghui Wang · Feb 24, 2026 · Citations: 0
Automatic Metrics Long Horizon
Large Language Model (LLM) agents are susceptible to Indirect Prompt Injection (IPI) attacks, where malicious instructions in retrieved content hijack the agent's execution.
- Search-P1: Path-Centric Reward Shaping for Stable and Efficient Agentic RAG Training
Tianle Xia, Ming Xu, Lingxiang Hu, Yiding Sun, Wenwei Li · Feb 26, 2026 · Citations: 0
Automatic Metrics Long Horizon
We propose Search-P1, a framework that introduces path-centric reward shaping for agentic RAG training, comprising two key components: (1) Path-Centric Reward, which evaluates the structural quality of reasoning trajectories through…
- VIGiA: Instructional Video Guidance via Dialogue Reasoning and Retrieval
Diogo Glória-Silva, David Semedo, João Maglhães · Feb 22, 2026 · Citations: 0
Automatic Metrics Long Horizon
Our evaluation shows that VIGiA outperforms existing state-of-the-art models on all tasks in a conversational plan guidance setting, reaching over 90\% accuracy on plan-aware VQA.
- DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation
Hao Zheng, Guozhao Mo, Xinru Yan, Qianhao Yuan, Wenkai Zhang · Feb 26, 2026 · Citations: 0
Automatic Metrics Long Horizon
However, existing presentation agents often rely on predefined workflows and fixed templates.
- 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 · Citations: 0
Automatic Metrics Long Horizon
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…
- How Do Latent Reasoning Methods Perform Under Weak and Strong Supervision?
Yingqian Cui, Zhenwei Dai, Bing He, Zhan Shi, Hui Liu · Feb 25, 2026 · Citations: 0
Automatic Metrics Long Horizon
First, we observe pervasive shortcut behavior, where they achieve high accuracy without relying on latent reasoning.
- Hierarchical LLM-Based Multi-Agent Framework with Prompt Optimization for Multi-Robot Task Planning
Tomoya Kawabe, Rin Takano · Feb 25, 2026 · Citations: 0
Automatic Metrics Long Horizon
We present a hierarchical multi-agent LLM-based planner with prompt optimization: an upper layer decomposes tasks and assigns them to lower-layer agents, which generate PDDL problems solved by a classical planner.
- 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 · Citations: 0
Automatic Metrics Long Horizon
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.
- 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 · Citations: 0
Automatic Metrics Long Horizon
We propose TabAgent, a framework for replacing generative decision components in closed-set selection tasks with a compact textual-tabular classifier trained on execution traces.
- A Geometric Analysis of Small-sized Language Model Hallucinations
Emanuele Ricco, Elia Onofri, Lorenzo Cima, Stefano Cresci, Roberto Di Pietro · Feb 16, 2026 · Citations: 0
Automatic Metrics Long Horizon
Hallucinations -- fluent but factually incorrect responses -- pose a major challenge to the reliability of language models, especially in multi-step or agentic settings.
- Think like a Scientist: Physics-guided LLM Agent for Equation Discovery
Jianke Yang, Ohm Venkatachalam, Mohammad Kianezhad, Sharvaree Vadgama, Rose Yu · Feb 12, 2026 · Citations: 0
Automatic Metrics Long Horizon
We introduce KeplerAgent, an agentic framework that explicitly follows this scientific reasoning process.
- Provably Safe Generative Sampling with Constricting Barrier Functions
Darshan Gadginmath, Ahmed Allibhoy, Fabio Pasqualetti · Feb 24, 2026 · Citations: 0
Automatic Metrics Long Horizon
However, a critical gap remains for their deployment in safety-critical domains: the lack of formal guarantees that generated samples will satisfy hard constraints.
