1 citations · 1 across the 15 of their papers we have counts for
15 papers
CARD: Controlled Agentic Reddit Discussions for Credit Card Simulation
Yaoning Yu, Kai-Min Chang, Ye Yu +3
Online credit card discussions provide a natural setting for studying how consumers communicate about financial products. Simulating these discussions requires more than just gener…
KV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time Scaling
Peng Kuang, Haibo Jin, Xiaoyu Han +5
Process Reward Models (PRMs) have been proven to be highly effective in guiding test-time scaling (TTS) methods, which significantly boost the capabilities of LLM-based multi-agent…
Nemotron-Labs-Diffusion: A Tri-Mode Language Model Unifying Autoregressive, Diffusion, and Self-Speculation Decoding
Yonggan Fu, Lexington Whalen, Abhinav Garg +23
We introduce Nemotron-Labs-Diffusion, a tri-mode language model (LM) that unifies AR, diffusion, and self-speculation decoding within a single architecture. Trained with a joint AR…
Closing the Loop on Latent Reasoning via Test-Time Reconstruction
Xiaopeng Yuan, Haibo Jin, Ye Yu +4
Recent work moves intermediate reasoning from natural-language traces into latent or cache-level representations to reduce token overhead and avoid a discrete communication bottlen…
ThreadBench: Benchmarking Realism in Agentic Simulation of Real-world Discussions
Yaoning Yu, Ye Yu, Haojing Luo +4
LLM agents are increasingly used to simulate real-world interactions, but it remains unclear whether simulated behaviors preserve the content patterns and interaction dynamics of r…
Do Self-Evolving Agents Forget? Capability Degradation and Preservation in Lifelong LLM Agent Adaptation
Ye Yu, Xiaopeng Yuan, Haibo Jin +3
Recent advances in LLM agents enable systems that autonomously refine workflows, accumulate reusable skills, self-train their underlying models, and maintain persistent memory. How…
Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems
Ye Yu, Heming Liu, Haibo Jin +3
Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and orchestration while treating i…
Cachemir: Fully Homomorphic Encrypted Inference of Generative Large Language Model with KV Cache
Ye Yu, Yifan Zhou, Yi Chen +3
Generative large language models (LLMs) have revolutionized multiple domains. Modern LLMs predominantly rely on an autoregressive decoding strategy, which generates output tokens s…
Agent Primitives: Reusable Latent Building Blocks for Multi-Agent Systems
Haibo Jin, Peng Kuang, Ye Yu +2
While existing multi-agent systems (MAS) can handle complex problems by enabling collaboration among multiple agents, they are often highly task-specific, relying on manually craft…
Now You Hear Me: Audio Narrative Attacks Against Large Audio-Language Models
Ye Yu, Haibo Jin, Yaoning Yu +2
Large audio-language models increasingly operate on raw speech inputs, enabling more seamless integration across domains such as voice assistants, education, and clinical triage. T…
Synthetic Data-Driven Prompt Tuning for Financial QA over Tables and Documents
Yaoning Yu, Kai-Min Chang, Ye Yu +3
Financial documents like earning reports or balance sheets often involve long tables and multi-page reports. Large language models have become a new tool to help numerical reasonin…
PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Models
Ye Yu, Yaoning Yu, Haohan Wang
Large reasoning models (LRMs) such as Claude 3.7 Sonnet and OpenAI o1 achieve strong performance on mathematical benchmarks using lengthy chain-of-thought (CoT) reasoning, but the…
SIPDO: Closed-Loop Prompt Optimization via Synthetic Data Feedback
Yaoning Yu, Ye Yu, Peiyan Zhang +3
Prompt quality plays a critical role in the performance of large language models (LLMs), motivating a growing body of work on prompt optimization. Most existing methods optimize pr…
Model Risk Management for Generative AI In Financial Institutions
Anwesha Bhattacharyya, Ye Yu, Hanyu Yang +4
The success of OpenAI's ChatGPT in 2023 has spurred financial enterprises into exploring Generative AI applications to reduce costs or drive revenue within different lines of busin…
LeakAgent: RL-based Red-teaming Agent for LLM Privacy Leakage
Yuzhou Nie, Zhun Wang, Ye Yu +4
Recent studies have discovered that large language models (LLM) may be ``fooled'' to output private information, including training data, system prompts, and personally identifiabl…