- AD-Bench: A Real-World, Trajectory-Aware Advertising Analytics Benchmark for LLM Agents
Lingxiang Hu, Yiding Sun, Tianle Xia, Wenwei Li, Ming Xu · Feb 15, 2026 · Citations: 0
Expert Verification Simulation Env Long Horizon
While Large Language Model (LLM) agents have achieved remarkable progress in complex reasoning tasks, evaluating their performance in real-world environments has become a critical problem.
- CricBench: A Multilingual Benchmark for Evaluating LLMs in Cricket Analytics
Vaibhav Devraj, Dhruv Kumar, Jagat Sesh Challa, Parth Agarwal, Navya Kommuri · Dec 26, 2025 · Citations: 0
Expert Verification Automatic Metrics
To investigate this potential capability gap, we present CricBench, a comprehensive benchmark suite for evaluating LLMs on specialized cricket data.
- Team of Thoughts: Efficient Test-time Scaling of Agentic Systems through Orchestrated Tool Calling
Jeffrey T. H. Wong, Zixi Zhang, Junyi Liu, Yiren Zhao · Feb 18, 2026 · Citations: 0
Expert Verification Multi Agent
Existing Multi-Agent Systems (MAS) typically rely on static, homogeneous model configurations, limiting their ability to exploit the distinct strengths of differently post-trained models.
- SparkMe: Adaptive Semi-Structured Interviewing for Qualitative Insight Discovery
David Anugraha, Vishakh Padmakumar, Diyi Yang · Feb 24, 2026 · Citations: 0
Expert Verification Automatic Metrics Multi Agent
Based on this formulation, we introduce SparkMe, a multi-agent LLM interviewer that performs deliberative planning via simulated conversation rollouts to select questions with high expected utility.
- PrivMedChat: End-to-End Differentially Private RLHF for Medical Dialogue Systems
Sudip Bhujel · Mar 3, 2026 · Citations: 0
Pairwise PreferenceExpert Verification Automatic Metrics
Conventional supervised fine-tuning and reinforcement learning from human feedback (RLHF) can amplify memorization risks, enabling empirical membership inference and extraction of rare training-set content.
- MEDSYN: Benchmarking Multi-EviDence SYNthesis in Complex Clinical Cases for Multimodal Large Language Models
Boqi Chen, Xudong Liu, Jiachuan Peng, Marianne Frey-Marti, Bang Zheng · Feb 25, 2026 · Citations: 0
Expert Verification Automatic Metrics
Multimodal large language models (MLLMs) have shown great potential in medical applications, yet existing benchmarks inadequately capture real-world clinical complexity.
- SurGo-R1: Benchmarking and Modeling Contextual Reasoning for Operative Zone in Surgical Video
Guanyi Qin, Xiaozhen Wang, Zhu Zhuo, Chang Han Low, Yuancan Xiao · Feb 25, 2026 · Citations: 0
Expert Verification Automatic Metrics
Existing AI systems offer binary safety verification or static detection, ignoring the phase-dependent nature of intraoperative reasoning.
- Demonstrating ViviDoc: Generating Interactive Documents through Human-Agent Collaboration
Yinghao Tang, Yupeng Xie, Yingchaojie Feng, Tingfeng Lan, Wei Chen · Mar 2, 2026 · Citations: 0
Expert Verification Multi Agent
Recent LLM-based agents can automate content creation, but naively applying them yields uncontrollable and unverifiable outputs.
- ExpGuard: LLM Content Moderation in Specialized Domains
Minseok Choi, Dongjin Kim, Seungbin Yang, Subin Kim, Youngjun Kwak · Mar 3, 2026 · Citations: 0
Expert Verification
With the growing deployment of large language models (LLMs) in real-world applications, establishing robust safety guardrails to moderate their inputs and outputs has become essential to ensure adherence to safety policies.
- Learning beyond Teacher: Generalized On-Policy Distillation with Reward Extrapolation
Wenkai Yang, Weijie Liu, Ruobing Xie, Kai Yang, Saiyong Yang · Feb 12, 2026 · Citations: 0
Expert Verification
Then, we propose the Generalized On-Policy Distillation (G-OPD) framework, which extends the standard OPD objective by introducing a flexible reference model and a reward scaling factor that controls the relative weight of the reward term…
