- 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.
- 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.
- Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation
Arthur Jakobsson, Abhinav Mahajan, Karthik Pullalarevu, Krishna Suresh, Yunchao Yao · Apr 23, 2026 · Citations: 0
Automatic MetricsSimulation Env Long Horizon
To mitigate this, we present a novel approach that leverages learned simulation priors to inform goal-conditioned dynamic manipulation of ropes for efficient and accurate task execution.
- Social Dynamics as Critical Vulnerabilities that Undermine Objective Decision-Making in LLM Collectives
Changgeon Ko, Jisu Shin, Hoyun Song, Huije Lee, Eui Jun Hwang · Apr 7, 2026 · Citations: 0
Automatic MetricsSimulation Env Multi Agent
Large language model (LLM) agents are increasingly acting as human delegates in multi-agent environments, where a representative agent integrates diverse peer perspectives to make a final decision.
- SEAL: An Open, Auditable, and Fair Data Generation Framework for AI-Native 6G Networks
Sunder Ali Khowaja, Kapal Dev, Engin Zeydan, Madhusanka Liyanage · Apr 2, 2026 · Citations: 0
Automatic MetricsSimulation Env
In this regard, we propose the Synthetic Data Generation with Ethics Audit Loop (SEAL) framework, which extends baseline modular pipelines with an Ethical and Regulatory Compliance by Design (ERCD) module and a Federated Learning (FL)…
- OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language Environment Simulation
Xiaomeng Hu, Yinger Zhang, Fei Huang, Jianhong Tu, Yang Su · Apr 13, 2026 · Citations: 0
Simulation Env Multi Agent
We introduce OccuBench, a benchmark covering 100 real-world professional task scenarios across 10 industry categories and 65 specialized domains, enabled by Language Environment Simulators (LESs) that simulate domain-specific environments…
- ActionParty: Multi-Subject Action Binding in Generative Video Games
Alexander Pondaven, Ziyi Wu, Igor Gilitschenski, Philip Torr, Sergey Tulyakov · Apr 2, 2026 · Citations: 0
Automatic MetricsSimulation Env Multi Agent
However, these models are largely restricted to single-agent settings, failing to control multiple agents simultaneously in a scene.
- 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.
- Heterogeneous Debate Engine: Identity-Grounded Cognitive Architecture for Resilient LLM-Based Ethical Tutoring
Jakub Masłowski, Jarosław A. Chudziak · Mar 28, 2026 · Citations: 0
Simulation Env Multi Agent
Large Language Models (LLMs) are being increasingly used as autonomous agents in complex reasoning tasks, opening the niche for dialectical interactions.
- Learning to Play Blackjack: A Curriculum Learning Perspective
Amirreza Alasti, Efe Erdal, Yücel Celik, Theresa Eimer · Mar 31, 2026 · Citations: 0
Automatic MetricsSimulation Env
We propose a novel framework that uses a Large Language Model (LLM) to dynamically generate a curriculum over available actions, enabling the agent to incorporate each action individually.
- Sell More, Play Less: Benchmarking LLM Realistic Selling Skill
Xuanbo Su, Wenhao Hu, Haibo Su, Yunzhang Chen, Le Zhan · Apr 8, 2026 · Citations: 0
Human EvalSimulation Env
We introduce SalesLLM benchmark, a bilingual (ZH/EN) benchmark derived from realistic applications covering Financial Services and Consumer Goods, built from 30,074 scripted configurations and 1,805 curated multi-turn scenarios with…