arXiv AI
PatientHub: A Unified Framework for Patient Simulation
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arXiv AI
Jun 18
Are LLMs Ready to Assist Physicians? PhysAssistBench for Interactive Doctor-Patient-EHR Assistance
arXiv:2606. 18613v1 Announce Type: cross Abstract: The most plausible near-term role of medical LLMs is to assist rather than replace physicians, yet current evaluations often test isolated capabilities: clinical knowledge, EHR system interaction, or patient communication.
arXiv AI
Jun 17
Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure
arXiv:2606. 17441v1 Announce Type: cross Abstract: Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and expensive user studies.
arXiv AI
Jun 16
State-Grounded Multi-Agent Synthetic Data Generation for Tool-Augmented LLMs
arXiv:2606. 16307v1 Announce Type: new Abstract: Training tool-augmented LLM agents requires large corpora of multi-turn, tool-grounded conversational data that is expensive to annotate, privacy-constrained in production settings, and largely absent from public datasets.
arXiv AI
Aug 14
PatientAct: Theory-Grounded Mental Health Client Simulation
arXiv:2608. 12750v1 Announce Type: cross Abstract: LLM-based simulated clients are increasingly used to train novice counselors, evaluate LLM therapists, and generate synthetic data.
arXiv AI
Aug 26
Simthesizer: An Agent-Driven Simulation Framework for LLM Serving Systems
arXiv:2608.24650v1 Announce Type: cross Abstract: System-level simulation is an essential tool for exploring the rapidly expanding design space of LLM serving systems, where real deployments remain c...
arXiv AI
Sep 3
UniToolCall: Unifying Tool-Use Representation, Data, and Evaluation for LLM Agents
UniToolCall introduces a unified framework for tool-use in large language model agents, standardizing toolset construction, dataset generation, and evaluation. The framework aggregates over 22,000 tools and creates a hybrid training corpus of more than 390,000 instances by combining ten public datasets with synthetically generated, structurally controlled trajectories. It models diverse interaction patterns—single‑hop vs. multi‑hop, single‑turn vs. multi‑turn, serial vs. parallel execution—and adds an Anchor Linkage mechanism to enforce cross‑turn dependencies, while converting seven public benchmarks into a common Query–Action–Observation–Answer format for fine‑grained evaluation.