LLM Digest

Story

arxiv_agent_systems_research · Oct 23, 2026 · paper

Source brief

Profile-Driven User Simulation via Reinforcement Learning with Hierarchical Rewards for Task-Oriented Dialogues

arxiv.orgOct 23, 2026
original source linked

In brief

Building Task-Oriented Dialogue (TOD) systems for high-value scenarios such as financial marketing requires large volumes of domain-specific dialogue data, which privacy regulations, annotation costs, and the need for...

Feed lens

agentevaluation

Read the original at arxiv.org →Open in live feed Read that day’s brief

Profile-Driven User Simulation via Reinforcement Learning with Hierarchical Rewards for Task-Oriented Dialogues

Earlier in this thread 4 items

DelTA: Discriminative Token Credit Assignment for Reinforcement Learning from Verifiable Rewards

Selector-Guided Autonomous Curriculum for One-Shot Reinforcement Learning from Verifiable Rewards

SWE-DIVE: Multi-Turn Coding Agent Evaluation with Dynamic User Simulation

Measure First, Then Allocate: Calibrated Rollout Budgets for MCP Agents in Reinforcement Learning