- AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications
Yujie Zhao, Boqin Yuan, Junbo Huang, Haocheng Yuan, Zhongming Yu · Feb 26, 2026 · Citations: 0
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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
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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 --…
- 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
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Recent deep research agents primarily improve performance by scaling reasoning depth, but this leads to high inference cost and latency in search-intensive scenarios.
- BankMathBench: A Benchmark for Numerical Reasoning in Banking Scenarios
Yunseung Lee, Subin Kim, Youngjun Kwak, Jaegul Choo · Feb 19, 2026 · Citations: 0
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However, such errors have rarely been captured by existing benchmarks.
- The Sufficiency-Conciseness Trade-off in LLM Self-Explanation from an Information Bottleneck Perspective
Ali Zahedzadeh, Behnam Bahrak · Feb 15, 2026 · Citations: 0
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Building on the information bottleneck principle, we conceptualize explanations as compressed representations that retain only the information essential for producing correct answers.To operationalize this view, we introduce an evaluation…
- 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 · Citations: 0
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The rapid development of large language model (LLM)-based agents has unlocked new possibilities for autonomous multi-turn reasoning and tool-augmented decision-making.
- 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 · Citations: 0
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This modular pipeline separates exploration (diffusion) from evaluation and solution synthesis, avoiding monolithic unified hybrids while preserving broad search.
- GATES: Self-Distillation under Privileged Context with Consensus Gating
Alex Stein, Furong Huang, Tom Goldstein · Feb 24, 2026 · Citations: 0
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Held-out in-domain accuracy under asymmetric evaluation improves from 46.0\% to 62.0\%, and average (maj@8) accuracy on public document-free math benchmarks improves from 20.2\% to 35.4\%.
- Continuous Telemonitoring of Heart Failure using Personalised Speech Dynamics
Yue Pan, Xingyao Wang, Hanyue Zhang, Liwei Liu, Changxin Li · Feb 23, 2026 · Citations: 0
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.
- 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
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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
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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.
- AgenticRAGTracer: A Hop-Aware Benchmark for Diagnosing Multi-Step Retrieval Reasoning in Agentic RAG
Qijie You, Wenkai Yu, Wentao Zhang · Feb 22, 2026 · Citations: 0
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With the rapid advancement of agent-based methods in recent years, Agentic RAG has undoubtedly become an important research direction.
- 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
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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
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First, we observe pervasive shortcut behavior, where they achieve high accuracy without relying on latent reasoning.
- GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL
Rui Yang, Qianhui Wu, Zhaoyang Wang, Hanyang Chen, Ke Yang · Feb 25, 2026 · Citations: 0
Automatic Metrics Coding
Open-source native GUI agents still lag behind closed-source systems on long-horizon navigation tasks.
- Hierarchical LLM-Based Multi-Agent Framework with Prompt Optimization for Multi-Robot Task Planning
Tomoya Kawabe, Rin Takano · Feb 25, 2026 · Citations: 0
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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.
- Classroom Final Exam: An Instructor-Tested Reasoning Benchmark
Chongyang Gao, Diji Yang, Shuyan Zhou, Xichen Yan, Luchuan Song · Feb 23, 2026 · Citations: 0
Automatic Metrics Coding
We introduce (Classroom Final Exam), a multimodal benchmark for evaluating the reasoning capabilities of large language models across more than 20 STEM domains.
- 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
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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.
- 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
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We introduce KeplerAgent, an agentic framework that explicitly follows this scientific reasoning process.
- Conflict-Aware Fusion: Resolving Logic Inertia in Large Language Models via Structured Cognitive Priors
Qiming Bao, Xiaoxuan Fu, Michael Witbrock · Dec 6, 2025 · Citations: 0
Automatic Metrics Law
We present a controlled evaluation framework consisting of four stress tests: (1) rule deletion (redundant vs.
