13 citations · 21 across the 6 of their papers we have counts for
7 papers
VRL-Bench: Benchmarking agents on computer control tasks under finite trial budgets
Yu Bai, Yukai Miao, Dawei Wang +8
Learning from trial and error is a promising way to improve language agents on complex tasks such as computer control. Reflexion introduced verbal reinforcement learning, which tur…
EntWorld: A Holistic Environment and Benchmark for Verifiable Enterprise GUI Agents
Ying Mo, Yu Bai, Dapeng Sun +4
Recent advances in Multimodal Large Language Models (MLLMs) have enabled agents to operate in open-ended web and operating system environments. However, existing benchmarks predomi…
DMA: Online RAG Alignment with Human Feedback
Yu Bai, Yukai Miao, Dawei Wang +9
Retrieval-augmented generation (RAG) systems often rely on static retrieval, limiting adaptation to evolving intent and content drift. We introduce Dynamic Memory Alignment (DMA),…
Quasi-Orthogonality and Polysemy: The Limits of Quantum Analogy in Large Language Models
Karl Svozil
We analyze two geometric aspects of meaning-sensitive behavior in next-token models. First, high-dimensional geometry permits exponentially many nearly orthogonal feature direction…
ProphetFuzz: Fully Automated Prediction and Fuzzing of High-Risk Option Combinations with Only Documentation via Large Language Model
Dawei Wang, Geng Zhou, Li Chen +2
Vulnerabilities related to option combinations pose a significant challenge in software security testing due to their vast search space. Previous research primarily addressed this…
Pistis-RAG: Enhancing Retrieval-Augmented Generation with Human Feedback
Yu Bai, Yukai Miao, Li Chen +6
RAG systems face limitations when semantic relevance alone does not guarantee improved generation quality. This issue becomes particularly evident due to the sensitivity of large l…
An Empirical Study of NetOps Capability of Pre-Trained Large Language Models
Yukai Miao, Yu Bai, Li Chen +10
Nowadays, the versatile capabilities of Pre-trained Large Language Models (LLMs) have attracted much attention from the industry. However, some vertical domains are more interested…