activity
20192026
most citedDeconfounded Causal Collaborative Filtering

39 citations · 136 across the 60 of their papers we have counts for

collaborators

63 papers

cs.CL2026

MMedAgent-Plus: Scaling Multimodal Medical Agents across Modalities, Tasks and Workflows

Ruoxin Wang, Yuanting Pan, Binxu Li +13

Medical workflows often require multiple interdependent analyses, but existing specialist and generalist AI models are not designed to coordinate them. We introduce MMedAgent-Plus,…

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.CL2026

Salesforce Koa: An Enterprise Language Model for Agentic Tool Use

Zixiang Chen, Sufeng Niu, Yingchi Liu +23

We present Salesforce Koa, an enterprise language model built by post-training the open-weight Nemotron-3-Super-120B foundation model with reinforcement learning using Group Relati…

cs.CL2026

Random Attention: Rethinking KV Cache Eviction for Efficient Reasoning

Heng Wang, Jielin Qiu, Wenting Zhao +8

Large language models achieve superior performance on tasks that require extended reasoning, but long chains of thought make the KV cache a severe memory bottleneck. Existing KV ca…

cs.LG2026

AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses

Cheng Qian, Wenting Zhao, Liangwei Yang +6

Recent work on distillation transfers the capabilities of large models to smaller ones often by updating the latter's parameters, through teacher forcing, on-policy distillation, a…

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.HC2026

RealUserSim: Bridging the Reality Gap in Agent Benchmarking via Grounded User Simulation

Ming Zhu, Juntao Tan, Rithesh Murthy +6

LLM-based user simulation is the primary mechanism for end-to-end agent evaluation, yet simulated users are poor proxies for real humans: unconstrained LLM defaults produce a Forma…

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.SD2026

Building Enterprise Realtime Voice Agents from Scratch: A Technical Tutorial

Jielin Qiu, Zixiang Chen, Liangwei Yang +11

We present a technical tutorial for building enterprise-grade realtime voice agents from first principles. While end-to-end speech-to-speech models may ultimately provide the best…

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

A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agents

Wei-Chieh Huang, Weizhi Zhang, Yueqing Liang +56

Research in artificial intelligence is shifting from model innovations and benchmark scores towards problem definition and rigorous real-world evaluation. As the field enters the "…

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.RO2025

Robotic VLA Benefits from Joint Learning with Motion Image Diffusion

Yu Fang, Kanchana Ranasinghe, Le Xue +10

Vision-Language-Action (VLA) models have achieved remarkable progress in robotic manipulation by mapping multimodal observations and instructions directly to actions. However, they…

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.LG2025

GeoGNN: Quantifying and Mitigating Semantic Drift in Text-Attributed Graphs

Liangwei Yang, Jing Ma, Jianguo Zhang +11

Graph neural networks (GNNs) on text--attributed graphs (TAGs) typically encode node texts using pretrained language models (PLMs) and propagate these embeddings through linear nei…

cs.LG2025

Test-Time Adaptation for LLM Agents via Environment Interaction

Arthur Chen, Zuxin Liu, Jianguo Zhang +6

Large language model (LLM)-based agents struggle to generalize to novel and complex environments, such as unseen websites or new sets of functions, due to a fundamental mismatch be…

cs.LG2025

xRouter: Training Cost-Aware LLMs Orchestration System via Reinforcement Learning

Cheng Qian, Zuxin Liu, Shirley Kokane +10

Modern LLM deployments confront a widening cost-performance spectrum: premium models deliver strong reasoning but are expensive, while lightweight models are economical yet brittle…

cs.CL2025

ToolLibGen: Scalable Automatic Tool Creation and Aggregation for LLM Reasoning

Murong Yue, Zhiwei Liu, Liangwei Yang +8

Large Language Models (LLMs) equipped with external tools have demonstrated enhanced performance on complex reasoning tasks. The widespread adoption of this tool-augmented reasonin…

cs.LG2025

CoDA: Coding LM via Diffusion Adaptation

Haolin Chen, Shiyu Wang, Can Qin +12

Diffusion language models promise bidirectional context and infilling capabilities that autoregressive coders lack, yet practical systems remain heavyweight. We introduce CoDA, a 1…

cs.AI2025

UserRL: Training Interactive User-Centric Agent via Reinforcement Learning

Cheng Qian, Zuxin Liu, Akshara Prabhakar +10

Reinforcement learning (RL) has shown promise in training agentic models that move beyond static benchmarks to engage in dynamic, multi-turn interactions. Yet, the ultimate value o…

cs.SE2025

LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software Engineering

Jielin Qiu, Zuxin Liu, Zhiwei Liu +14

The emergence of long-context language models with context windows extending to millions of tokens has created new opportunities for sophisticated code understanding and software d…