3 citations · 3 across the 4 of their papers we have counts for
4 papers
Bench2Robust: Scenario-Controlled Recovery for Tool-Using Agents
Chaoran Chen, Vy Nguyen, Ziji Zhang +7
Tool-using LLM agents are typically developed and post-trained in controlled environments with reliable tools, but deployment exposes them to tool failures, API and schema drift, a…
Adaptive Layerwise Perturbation: Unifying Off-Policy Corrections for LLM RL
Chenlu Ye, Xuanchang Zhang, Yifan Hao +6
Off-policy problems such as policy staleness and training--inference mismatch have become a major bottleneck for training stability and further exploration in LLM RL. The distribut…
TOD-ProcBench: Benchmarking Complex Instruction-Following in Task-Oriented Dialogues
Sarik Ghazarian, Abhinav Gullapalli, Swair Shah +4
In real-world task-oriented dialogue (TOD) settings, agents are required to strictly adhere to complex instructions while conducting multi-turn conversations with customers. These…
FiNER-ORD: Financial Named Entity Recognition Open Research Dataset
Agam Shah, Abhinav Gullapalli, Ruchit Vithani +2
Over the last two decades, the development of the CoNLL-2003 named entity recognition (NER) dataset has helped enhance the capabilities of deep learning and natural language proces…