- AgentHER: Hindsight Experience Replay for LLM Agent Trajectory Relabeling
Liang Ding · Mar 22, 2026 · Citations: 0
Demonstrations Human EvalLlm As Judge Long Horizon
LLM agents fail on the majority of real-world tasks -- GPT-4o succeeds on fewer than 15% of WebArena navigation tasks and below 55% pass@1 on ToolBench (Zhou et al., 2024; Qin et al., 2024) -- yet every failed trajectory is routinely…
- TraceSafe: A Systematic Assessment of LLM Guardrails on Multi-Step Tool-Calling Trajectories
Yen-Shan Chen, Sian-Yao Huang, Cheng-Lin Yang, Yun-Nung Chen · Apr 8, 2026 · Citations: 0
Red Team Automatic Metrics Long Horizon
As large language models (LLMs) evolve from static chatbots into autonomous agents, the primary vulnerability surface shifts from final outputs to intermediate execution traces.
- When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation
Henry Peng Zou, Chunyu Miao, Wei-Chieh Huang, Yankai Chen, Yue Zhou · Apr 1, 2026 · Citations: 0
Critique Edit Simulation Env Long Horizon
As LLM agents transition from short, static problem solving to executing complex, long-horizon tasks in dynamic environments, the ability to handle user interruptions, such as adding requirement or revising goals, during mid-task execution…
- SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning
Philip Schroeder, Thomas Weng, Karl Schmeckpeper, Eric Rosen, Stephen Hart · Mar 30, 2026 · Citations: 0
Demonstrations Simulation Env Long Horizon
To address this limitation, we introduce SOLE-R1 (Self-Observing LEarner), a video-language reasoning model explicitly designed to serve as the sole reward signal for online RL.
- Signals: Trajectory Sampling and Triage for Agentic Interactions
Shuguang Chen, Adil Hafeez, Salman Paracha · Apr 1, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Long Horizon
We propose a lightweight, signal-based framework for triaging agentic interaction trajectories.
- Learning When to Act: Interval-Aware Reinforcement Learning with Predictive Temporal Structure
Davide Di Gioia · Mar 23, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Long Horizon
Autonomous agents operating in continuous environments must decide not only what to do, but when to act.
- Entropy trajectory shape predicts LLM reasoning reliability: A diagnostic study of uncertainty dynamics in chain-of-thought
Xinghao Zhao · Mar 19, 2026 · Citations: 0
Automatic Metrics Long Horizon
Chain-of-thought (CoT) reasoning improves LLM accuracy, yet detecting failures cheaply remains elusive.
- ReDAct: Uncertainty-Aware Deferral for LLM Agents
Dzianis Piatrashyn, Nikita Kotelevskii, Kirill Grishchenkov, Nikita Glazkov, Ivan Nasonov · Apr 8, 2026 · Citations: 0
Simulation Env Long Horizon
Recently, LLM-based agents have become increasingly popular across many applications, including complex sequential decision-making problems.
- RASPRef: Retrieval-Augmented Self-Supervised Prompt Refinement for Large Reasoning Models
Rahul Soni · Mar 27, 2026 · Citations: 0
Critique Edit Long Horizon
Recent reasoning-focused language models such as DeepSeek R1 and OpenAI o1 have demonstrated strong performance on structured reasoning benchmarks including GSM8K, MATH, and multi-hop question answering tasks.
- FrontierFinance: A Long-Horizon Computer-Use Benchmark of Real-World Financial Tasks
Michael Krumdick, Varshini Reddy, Shivani Chaudhary, William Day, Maarij Ahmed · Apr 7, 2026 · Citations: 0
Rubric Rating Long Horizon
To address this, we introduce FrontierFinance, a long-horizon benchmark of 25 complex financial modeling tasks across five core finance models, requiring an average of over 18 hours of skilled human labor per task to complete.
- TREX: Trajectory Explanations for Multi-Objective Reinforcement Learning
Dilina Rajapakse, Juan C. Rosero, Ivana Dusparic · Mar 23, 2026 · Citations: 0
Pairwise Preference Long Horizon
Multi-Objective Reinforcement Learning (MORL) addresses this limitation by enabling agents to optimize several objectives simultaneously, explicitly reasoning about trade-offs between them.
- DataSTORM: Deep Research on Large-Scale Databases using Exploratory Data Analysis and Data Storytelling
Shicheng Liu, Yucheng Jiang, Sajid Farook, Camila Nicollier Sanchez, David Fernando Castro Pena · Apr 7, 2026 · Citations: 0
Human Eval Long Horizon
Deep research with Large Language Model (LLM) agents is emerging as a powerful paradigm for multi-step information discovery, synthesis, and analysis.
- Kernel-Smith: A Unified Recipe for Evolutionary Kernel Optimization
He Du, Qiming Ge, Jiakai Hu, Aijun Yang, Zheng Cai · Mar 30, 2026 · Citations: 0
Critique Edit Long Horizon
We present Kernel-Smith, a framework for high-performance GPU kernel and operator generation that combines a stable evaluation-driven evolutionary agent with an evolution-oriented post-training recipe.
- Reasoning or Rhetoric? An Empirical Analysis of Moral Reasoning Explanations in Large Language Models
Aryan Kasat, Smriti Singh, Aman Chadha, Vinija Jain · Mar 23, 2026 · Citations: 0
Llm As Judge Long Horizon
Using an LLM-as-judge scoring pipeline validated across three judge models, we classify more than 600 responses from 13 LLMs spanning a range of architectures, parameter scales, and training regimes across six classical moral dilemmas, and…
- Spatio-Temporal Attention Enhanced Multi-Agent DRL for UAV-Assisted Wireless Networks with Limited Communications
Che Chen, Lanhua Li, Shimin Gong, Yu Zhao, Yuming Fang · Mar 23, 2026 · Citations: 0
Simulation Env Long Horizon
To maximize the overall throughput, we first propose a delay-tolerant multi-agent deep reinforcement learning (MADRL) algorithm that integrates a delay-penalized reward to encourage information sharing among UAVs, while jointly optimizing…
- Self-Debias: Self-correcting for Debiasing Large Language Models
Xuan Feng, Shuai Zhao, Luwei Xiao, Tianlong Gu, Bo An · Apr 9, 2026 · Citations: 0
Pairwise Preference Long Horizon
Unlike standard preference optimization which applies broad penalties, Self-Debias employs a fine-grained trajectory-level objective subject to dynamic debiasing constraints.
- Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning
Shiwan Zhao, Zhihu Wang, Xuyang Zhao, Jiaming Zhou, Caiyue Xu · Apr 9, 2026 · Citations: 0
Pairwise Preference Long Horizon
Recent progress spans supervised fine-tuning (SFT), preference optimization, reinforcement learning (RL), process supervision, verifier-guided methods, distillation, and multi-stage pipelines.
- The Ultimate Tutorial for AI-driven Scale Development in Generative Psychometrics: Releasing AIGENIE from its Bottle
Lara Russell-Lasalandra, Hudson Golino, Luis Eduardo Garrido, Alexander P. Christensen · Mar 30, 2026 · Citations: 0
Critique Edit Tool Use
Psychological scale development has traditionally required extensive expert involvement, iterative revision, and large-scale pilot testing before psychometric evaluation can begin.
- AgenticRec: End-to-End Tool-Integrated Policy Optimization for Ranking-Oriented Recommender Agents
Tianyi Li, Zixuan Wang, Guidong Lei, Xiaodong Li, Hui Li · Mar 23, 2026 · Citations: 0
Pairwise Preference Tool Use
To address this, we present AgenticRec, a ranking-oriented agentic recommendation framework that optimizes the entire decision-making trajectory (including intermediate reasoning, tool invocation, and final ranking list generation) under…
- HISR: Hindsight Information Modulated Segmental Process Rewards For Multi-turn Agentic Reinforcement Learning
Zhicong Lu, Zichuan Lin, Wei Jia, Changyuan Tian, Deheng Ye · Mar 19, 2026 · Citations: 0
Pairwise Preference Long Horizon
While large language models excel in diverse domains, their performance on complex longhorizon agentic decision-making tasks remains limited.
- Don't Overthink It: Inter-Rollout Action Agreement as a Free Adaptive-Compute Signal for LLM Agents
Khushal Sethi · Apr 9, 2026 · Citations: 0
Automatic Metrics Long Horizon
We introduce TrACE (Trajectorical Adaptive Compute via agrEement), a training-free controller that allocates LLM calls adaptively across agent timesteps by measuring inter-rollout action agreement.
- MemMachine: A Ground-Truth-Preserving Memory System for Personalized AI Agents
Shu Wang, Edwin Yu, Oscar Love, Tom Zhang, Tom Wong · Apr 6, 2026 · Citations: 0
Automatic Metrics Long Horizon
Large Language Model (LLM) agents require persistent memory to maintain personalization, factual continuity, and long-horizon reasoning, yet standard context-window and retrieval-augmented generation (RAG) pipelines degrade over…
- OSCAR: Orchestrated Self-verification and Cross-path Refinement
Yash Shah, Abhijit Chakraborty, Naresh Kumar Devulapally, Vishnu Lokhande, Vivek Gupta · Apr 2, 2026 · Citations: 0
Automatic Metrics Long Horizon
We introduce a suite of trajectory-level assessments, including a cross-chain divergence-at-hallucination (CDH) metric, for principled comparison of localization methods.
- S0 Tuning: Zero-Overhead Adaptation of Hybrid Recurrent-Attention Models
Jack Young · Apr 1, 2026 · Citations: 0
Automatic Metrics Long Horizon
Using roughly 48 execution-verified HumanEval training solutions, tuning a single initial state matrix per recurrent layer, with zero inference overhead, outperforms LoRA by +10.8 pp (p < 0.001) on HumanEval.
- Asymmetric Actor-Critic for Multi-turn LLM Agents
Shuli Jiang, Zhaoyang Zhang, Yi Zhang, Shuo Yang, Wei Xia · Mar 31, 2026 · Citations: 0
Automatic Metrics Long Horizon
In many real-world applications, agents must succeed in one-shot settings where retries are impossible.
- EnterpriseLab: A Full-Stack Platform for developing and deploying agents in Enterprises
Ankush Agarwal, Harsh Vishwakarma, Suraj Nagaje, Chaitanya Devaguptapu · Mar 23, 2026 · Citations: 0
Automatic Metrics Long Horizon
Deploying AI agents in enterprise environments requires balancing capability with data sovereignty and cost constraints.
- MolQuest: A Benchmark for Agentic Evaluation of Abductive Reasoning in Chemical Structure Elucidation
Taolin Han, Shuang Wu, Jinghang Wang, Yuhao Zhou, Renquan Lv · Mar 26, 2026 · Citations: 0
Automatic MetricsSimulation Env Long Horizon
Current scientific evaluation benchmarks predominantly rely on static, single-turn Question Answering (QA) formats, which are inadequate for measuring model performance in complex scientific tasks that require multi-step iteration and…
- TSUBASA: Improving Long-Horizon Personalization via Evolving Memory and Self-Learning with Context Distillation
Xinliang Frederick Zhang, Lu Wang · Apr 9, 2026 · Citations: 0
Pairwise Preference Long Horizon
Personalized large language models (PLLMs) have garnered significant attention for their ability to align outputs with individual's needs and preferences.
- PASK: Toward Intent-Aware Proactive Agents with Long-Term Memory
Zhifei Xie, Zongzheng Hu, Fangda Ye, Xin Zhang, Haobo Chai · Apr 9, 2026 · Citations: 0
Automatic Metrics Long Horizon
Prior work remains largely confined to laboratory settings, leaving a clear gap in real-world proactive agent: depth, complexity, ambiguity, precision and real-time constraints.
- Full-Duplex-Bench-v3: Benchmarking Tool Use for Full-Duplex Voice Agents Under Real-World Disfluency
Guan-Ting Lin, Chen Chen, Zhehuai Chen, Hung-yi Lee · Apr 6, 2026 · Citations: 0
Automatic Metrics Tool Use
We introduce Full-Duplex-Bench-v3 (FDB-v3), a benchmark for evaluating spoken language models under naturalistic speech conditions and multi-step tool use.
- SkillX: Automatically Constructing Skill Knowledge Bases for Agents
Chenxi Wang, Zhuoyun Yu, Xin Xie, Wuguannan Yao, Runnan Fang · Apr 6, 2026 · Citations: 0
Automatic Metrics Long Horizon
Learning from experience is critical for building capable large language model (LLM) agents, yet prevailing self-evolving paradigms remain inefficient: agents learn in isolation, repeatedly rediscover similar behaviors from limited…
- $\texttt{YC-Bench}$: Benchmarking AI Agents for Long-Term Planning and Consistent Execution
Muyu He, Adit Jain, Anand Kumar, Vincent Tu, Soumyadeep Bakshi · Apr 1, 2026 · Citations: 0
Automatic Metrics Long Horizon
As LLM agents tackle increasingly complex tasks, a critical question is whether they can maintain strategic coherence over long horizons: planning under uncertainty, learning from delayed feedback, and adapting when early mistakes compound.
- Training LLMs for Multi-Step Tool Orchestration with Constrained Data Synthesis and Graduated Rewards
Cheng Jiayang, Xin Liu, Zhihan Zhang, Haoyang Wen, Zixuan Zhang · Mar 25, 2026 · Citations: 0
Automatic Metrics Long Horizon
We present a framework addressing both challenges.
- Effective Strategies for Asynchronous Software Engineering Agents
Jiayi Geng, Graham Neubig · Mar 23, 2026 · Citations: 0
Automatic Metrics Long Horizon
Inspired by these collaboration primitives, we introduce Centralized Asynchronous Isolated Delegation (CAID), a structured multi-agent coordination paradigm grounded in three core SWE primitives: centralized task delegation, asynchronous…
- Joint Optimization of Reasoning and Dual-Memory for Self-Learning Diagnostic Agent
Bingxuan Li, Simo Du, Yue Guo · Apr 8, 2026 · Citations: 0
Automatic Metrics Long Horizon
We propose SEA, a self-learning diagnostic agent with cognitively inspired dual-memory module.
- SHAPE: Stage-aware Hierarchical Advantage via Potential Estimation for LLM Reasoning
Zhengyang Ai, Zikang Shan, Xiaodong Ai, Jingxian Tang, Hangkai Hu · Apr 8, 2026 · Citations: 0
Automatic Metrics Long Horizon
Extensive experiments in math reasoning across three base models and five benchmarks demonstrate that SHAPE achieves an average accuracy gain of 3% with 30% reduced token consumption.
- Unifying Group-Relative and Self-Distillation Policy Optimization via Sample Routing
Gengsheng Li, Tianyu Yang, Junfeng Fang, Mingyang Song, Mao Zheng · Apr 2, 2026 · Citations: 0
Automatic Metrics Long Horizon
Evaluated across five benchmarks and two model scales, SRPO achieves both the rapid early improvement of SDPO and the long-horizon stability of GRPO.
- LEO: Graph Attention Network based Hybrid Multi Sensor Extended Object Fusion and Tracking for Autonomous Driving Applications
Mayank Mayank, Bharanidhar Duraisamy, Florian Geiss · Apr 2, 2026 · Citations: 0
Automatic Metrics Long Horizon
Evaluations on the Mercedes-Benz DRIVE PILOT SAE L3 dataset demonstrate real-time computational efficiency suitable for production systems; additional validation on public datasets such as View of Delft (VoD) further confirms cross-dataset…
- Scaling Reasoning Tokens via RL and Parallel Thinking: Evidence From Competitive Programming
Qianfan Zhang, Tianyu Guo, Xuandi Ren, Jiale Chen, Ming Ding · Apr 1, 2026 · Citations: 0
Automatic Metrics Long Horizon
During RL training, we observe an approximately log-linear relationship between validation accuracy and the average number of generated reasoning tokens over successive checkpoints, and show two ways to shift this training trajectory:…
- TRIMS: Trajectory-Ranked Instruction Masked Supervision for Diffusion Language Models
Lingjie Chen, Ruizhong Qiu, Yuyu Fan, Yanjun Zhao, Hanghang Tong · Apr 1, 2026 · Citations: 0
Automatic Metrics Long Horizon
Experiments on LLaDA and Dream across math and coding benchmarks show that TRIMS significantly improves the accuracy-parallelism trade-off over both standard MDLM training and train-free acceleration baselines, while achieving competitive…
- AgentSwing: Adaptive Parallel Context Management Routing for Long-Horizon Web Agents
Zhaopeng Feng, Liangcai Su, Zhen Zhang, Xinyu Wang, Xiaotian Zhang · Mar 29, 2026 · Citations: 0
Automatic Metrics Long Horizon
As large language models (LLMs) evolve into autonomous agents for long-horizon information-seeking, managing finite context capacity has become a critical bottleneck.
- S2D2: Fast Decoding for Diffusion LLMs via Training-Free Self-Speculation
Ligong Han, Hao Wang, Han Gao, Kai Xu, Akash Srivastava · Mar 26, 2026 · Citations: 0
Automatic Metrics Long Horizon
We present S2D2, a training-free self-speculative decoding framework for block-diffusion language models.
- The Evolution of Tool Use in LLM Agents: From Single-Tool Call to Multi-Tool Orchestration
Haoyuan Xu, Chang Li, Xinyan Ma, Xianhao Ou, Zihan Zhang · Mar 24, 2026 · Citations: 0
Automatic Metrics Tool Use
As agent systems evolve, however, the central problem has shifted from isolated invocation to multi-tool orchestration over long trajectories with intermediate state, execution feedback, changing environments, and practical constraints such…
- Progressive Training for Explainable Citation-Grounded Dialogue: Reducing Hallucination to Zero in English-Hindi LLMs
Vedant Pandya · Mar 19, 2026 · Citations: 0
Automatic Metrics Long Horizon
We present XKD-Dial, a progressive four-stage training pipeline for explainable, knowledge-grounded dialogue generation in a bilingual (English-Hindi) setting, comprising: (1) multilingual adaptation, (2) English dialogue SFT with citation…
- Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces
Jiawei Chen, Ruoxi Xu, Boxi Cao, Ruotong Pan, Yunfei Zhang · Apr 9, 2026 · Citations: 0
Simulation Env Long Horizon
However, existing benchmarks remain constrained to isolated scenarios, narrow action spaces, or synthetic data, failing to capture the holistic nature of authentic human behavior.
- From High-Dimensional Spaces to Verifiable ODD Coverage for Safety-Critical AI-based Systems
Thomas Stefani, Johann Maximilian Christensen, Elena Hoemann, Frank Köster, Sven Hallerbach · Apr 2, 2026 · Citations: 0
Simulation Env Long Horizon
While Artificial Intelligence (AI) offers transformative potential for operational performance, its deployment in safety-critical domains such as aviation requires strict adherence to rigorous certification standards.
- Verify Before You Commit: Towards Faithful Reasoning in LLM Agents via Self-Auditing
Wenhao Yuan, Chenchen Lin, Jian Chen, Jinfeng Xu, Xuehe Wang · Apr 9, 2026 · Citations: 0
Automatic Metrics Long Horizon
In large language model (LLM) agents, reasoning trajectories are treated as reliable internal beliefs for guiding actions and updating memory.
- Cognitive Loop of Thought: Reversible Hierarchical Markov Chain for Efficient Mathematical Reasoning
Jia-Chen Zhang, Zheng Zhou, Yu-Jie Xiong · Apr 8, 2026 · Citations: 0
Automatic Metrics Long Horizon
Inspired by human cognitive processes, we introduce a backward verification mechanism at each hierarchical layer.
- AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learning
Yuanfu Sun, Kang Li, Dongzhe Fan, Jiajin Liu, Qiaoyu Tan · Apr 7, 2026 · Citations: 0
Automatic Metrics Tool Use
To bridge this gap, we introduce Agentic Graph Learning (AGL), a paradigm that reframes graph learning as an interleaved process of topology-aware navigation and LLM-based inference.
- Novel Memory Forgetting Techniques for Autonomous AI Agents: Balancing Relevance and Efficiency
Payal Fofadiya, Sunil Tiwari · Apr 2, 2026 · Citations: 0
Automatic Metrics Long Horizon
Long-horizon conversational agents require persistent memory for coherent reasoning, yet uncontrolled accumulation causes temporal decay and false memory propagation.
- HippoCamp: Benchmarking Contextual Agents on Personal Computers
Zhe Yang, Shulin Tian, Kairui Hu, Shuai Liu, Hoang-Nhat Nguyen · Apr 1, 2026 · Citations: 0
Automatic Metrics Tool Use
We present HippoCamp, a new benchmark designed to evaluate agents' capabilities on multimodal file management.
- Oblivion: Self-Adaptive Agentic Memory Control through Decay-Driven Activation
Ashish Rana, Chia-Chien Hung, Qumeng Sun, Julian Martin Kunkel, Carolin Lawrence · Mar 31, 2026 · Citations: 0
Automatic Metrics Long Horizon
Human memory adapts through selective forgetting: experiences become less accessible over time but can be reactivated by reinforcement or contextual cues.
- Hierarchical Chain-of-Thought Prompting: Enhancing LLM Reasoning Performance and Efficiency
Xingshuai Huang, Derek Li, Bahareh Nikpour, Parsa Omidi · Mar 31, 2026 · Citations: 0
Automatic Metrics Long Horizon
Extensive evaluations across diverse LLMs and mathematical reasoning benchmarks show that Hi-CoT consistently improves average accuracy by 6.2% (up to 61.4% on certain models and tasks) while reducing reasoning trace length by 13.9%…
- PerceptionComp: A Video Benchmark for Complex Perception-Centric Reasoning
Shaoxuan Li, Zhixuan Zhao, Hanze Deng, Zirun Ma, Shulin Tian · Mar 27, 2026 · Citations: 0
Automatic Metrics Long Horizon
We introduce PerceptionComp, a manually annotated benchmark for complex, long-horizon, perception-centric video reasoning.
- Mi:dm K 2.5 Pro
KT Tech innovation Group · Mar 19, 2026 · Citations: 0
Automatic Metrics Long Horizon
The evolving LLM landscape requires capabilities beyond simple text generation, prioritizing multi-step reasoning, long-context understanding, and agentic workflows.
- Efficient Training-Free Multi-Token Prediction via Embedding-Space Probing
Raghavv Goel, Mukul Gagrani, Mingu Lee, Chris Lott · Mar 18, 2026 · Citations: 0
Automatic Metrics Long Horizon
Across benchmarks, our probing-based MTP consistently outperforms existing training-free baselines, increasing acceptance length by approximately 12\% on LLaMA3 and 8--12\% on Qwen3, and achieving throughput gains of up to 15--19\%.
- Governed Memory: A Production Architecture for Multi-Agent Workflows
Hamed Taheri · Mar 18, 2026 · Citations: 0
Automatic Metrics Long Horizon
Enterprise AI deploys dozens of autonomous agent nodes across workflows, each acting on the same entities with no shared memory and no common governance.
- Learning When to Attend: Conditional Memory Access for Long-Context LLMs
Sakshi Choudhary, Aditya Chattopadhyay, Luca Zancato, Elvis Nunez, Matthew Trager · Mar 18, 2026 · Citations: 0
Automatic Metrics Long Horizon
Based on this, we propose L2A (Learning To Attend), a layer that enables conditional (token-wise) long-range memory access by deciding when to invoke global attention.
- OpenVLThinkerV2: A Generalist Multimodal Reasoning Model for Multi-domain Visual Tasks
Wenbo Hu, Xin Chen, Yan Gao-Tian, Yihe Deng, Nanyun Peng · Apr 9, 2026 · Citations: 0
Long Horizon
Extensive evaluations across 18 diverse benchmarks demonstrate its superior performance over strong open-source and leading proprietary frontier models.
- ClawBench: Can AI Agents Complete Everyday Online Tasks?
Yuxuan Zhang, Yubo Wang, Yipeng Zhu, Penghui Du, Junwen Miao · Apr 9, 2026 · Citations: 0
Long Horizon
AI agents may be able to automate your inbox, but can they automate other routine aspects of your life?