19 citations · 24 across the 4 of their papers we have counts for
4 papers
Optimizing What Policies Learn From: Recoverability-aware Rollout Intervention Learning
Zheyuan Zhang, Manqing Mao, Hong Wang +8
Critic-free group-based reinforcement learning has become a scalable approach for post-training large language models. However, most existing methods allocate the same number of ro…
WISE-Flow: Workflow-Induced Structured Experience for Self-Evolving Conversational Service Agents
Yuqing Zhou, Zhuoer Wang, Jie Yuan +4
Large language model (LLM)-based agents are widely deployed in user-facing services but remain error-prone in new tasks, tend to repeat the same failure patterns, and show substant…
SpeechVerse: A Large-scale Generalizable Audio Language Model
Nilaksh Das, Saket Dingliwal, Srikanth Ronanki +14
Large language models (LLMs) have shown incredible proficiency in performing tasks that require semantic understanding of natural language instructions. Recently, many works have f…
Probing and Fine-tuning Reading Comprehension Models for Few-shot Event Extraction
Rui Feng, Jie Yuan, Chao Zhang
We study the problem of event extraction from text data, which requires both detecting target event types and their arguments. Typically, both the event detection and argument dete…