most citedEnterprise Sales Copilot: Enabling Real-Time AI Support with Automatic Information Retrieval in Live Sales Calls

1 citations · 1 across the 12 of their papers we have counts for

collaborators

12 papers

cs.LG2026

Critical-State RL: Diagnosing Trainable States for Multi-Turn Tool Use

Zixiang Chen, Wenting Zhao, Zhepeng Cen +9

Multi-turn tool-use failures can hinge on a single model call, yet reward variation alone does not reveal which call would benefit from training. When rewards depend on later inter…

cs.AI2026

JarvisGUI: Towards Cross-Device GUI Agents with Dynamic Task Composition

Zixiang Chen, Yuheng Lu, Zihao Cheng +8

Real-world GUI usage frequently involves workflows that span multiple devices and platforms, requiring the transfer of intermediate results, maintenance of shared state, and coordi…

cs.AI2026

BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces

Liangwei Yang, Jielin Qiu, Zixiang Chen +9

Many decision-support settings require systems that adapt to individual users, but evaluation data for this problem remain limited. Existing benchmarks for user understanding often…

cs.SD2026

Whisper-AuT: Domain-Adapted Audio Encoder for Efficient Audio-LLM Training

Jielin Qiu, Ming Zhu, Wenting Zhao +11

Audio-native large language models (audio-LLMs) commonly use Whisper as their audio encoder. However, Whisper was trained exclusively on speech data, producing weak representations…

cs.SD2026★ 1 cited

Enterprise Sales Copilot: Enabling Real-Time AI Support with Automatic Information Retrieval in Live Sales Calls

Jielin Qiu, Liangwei Yang, Ming Zhu +11

During live sales calls, customers frequently ask detailed product questions that require representatives to manually search internal databases and CRM systems. This process typica…

cs.CL2026

Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models

Liangwei Yang, Shiyu Wang, Haolin Chen +12

As large language models (LLMs) transition from research prototypes to real-world systems, customization has emerged as a central bottleneck. While text prompts can already customi…

cs.SD2026

VoiceAgentRAG: Solving the RAG Latency Bottleneck in Real-Time Voice Agents Using Dual-Agent Architectures

Jielin Qiu, Jianguo Zhang, Zixiang Chen +12

We present VoiceAgentRAG, an open-source dual-agent memory router that decouples retrieval from response generation. A background Slow Thinker agent continuously monitors the conve…

cs.SD2026

AudioCapBench: Quick Evaluation on Audio Captioning across Sound, Music, and Speech

Jielin Qiu, Jianguo Zhang, Zixiang Chen +13

We introduce AudioCapBench, a benchmark for evaluating audio captioning capabilities of large multimodal models. \method covers three distinct audio domains, including environmenta…

cs.CL2026

PlugMem: A Task-Agnostic Plugin Memory Module for LLM Agents

Ke Yang, Zixi Chen, Xuan He +6

Long-term memory is essential for large language model (LLM) agents operating in complex environments, yet existing memory designs are either task-specific and non-transferable, or…

cs.CL2026

Prompt Optimization Via Diffusion Language Models

Shiyu Wang, Haolin Chen, Liangwei Yang +8

We propose a diffusion-based framework for prompt optimization that leverages Diffusion Language Models (DLMs) to iteratively refine system prompts through masked denoising. By con…

cs.SE2025

LoCoBench-Agent: An Interactive Benchmark for LLM Agents in Long-Context Software Engineering

Jielin Qiu, Zuxin Liu, Zhiwei Liu +18

As large language models (LLMs) evolve into sophisticated autonomous agents capable of complex software development tasks, evaluating their real-world capabilities becomes critical…

cs.CL2025

Enterprise Deep Research: Steerable Multi-Agent Deep Research for Enterprise Analytics

Akshara Prabhakar, Roshan Ram, Zixiang Chen +5

As information grows exponentially, enterprises face increasing pressure to transform unstructured data into coherent, actionable insights. While autonomous agents show promise, th…