1 citations · 1 across the 10 of their papers we have counts for
8 papers · 1 filter
MSI-Bench: Evaluating Multi-Speaker Voice Interaction for Collaborative AI Agents
Chenxu Xiong, Dongming Shen, Yuzhi Tang +3
Voice provides a natural and immediate interface for AI agents. Many settings in which voice agents could be useful, including meetings, households, and collaborative work, are inh…
Alignment Drift in Single-Model Speculative Decoding for ASR: Mechanism, Correction, and Cost
Xinyu Wang, Huapeng Zhou, Ziyu Zhao +5
Speculative decoding speeds up generation by letting a cheap draft propose several tokens that a target model checks in one pass. In the single-model form, the draft is a lightweig…
Instruct-FD: Can Your Full-Duplex Speech System Follow Turn-Taking Instructions?
Yuzhi Tang, Wentao Ma, Xiling Zhao +17
Current full-duplex (FD) spoken dialogue systems can produce fluid interactions, yet it remains unclear whether they can adapt their turn-taking behavior when explicitly instructed…
IHBench: Evaluating Post-Interruption Recovery in Voice Agents with Structured Workflows
Ahmad Salimi, Wentao Ma, Yuzhi Tang +3
Voice agents deployed in structured workflows (customer service, healthcare scheduling, account management) must handle frequent user interruptions while maintaining progress throu…
Trust the Batch, On- or Off-Policy: Adaptive Policy Optimization for RL Post-Training
Rasool Fakoor, Murdock Aubry, Nicholas Stranges +1
Reinforcement learning is structurally harder than supervised learning because the policy changes the data distribution it learns from. The resulting fragility is especially visibl…
ProactBench: Beyond What The User Asked For
Sepehr Harfi, Ahmad Salimi, Dongming Shen +1
Most LLM benchmarks score how well a model responds to explicit requests. They leave unmeasured a different conversational ability: noticing and acting on needs the user has implie…