Jianguo Zhang

Orcid: 0009-0004-6972-4020

Affiliations:
  • Salesforce AI Research, USA
  • University of Illinois at Chicago, Department of Computer Science, IL, USA (PhD 2022)


According to our database1, Jianguo Zhang authored at least 57 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models.
CoRR, March, 2026

AudioCapBench: Quick Evaluation on Audio Captioning across Sound, Music, and Speech.
CoRR, February, 2026

2025
LoCoBench-Agent: An Interactive Benchmark for LLM Agents in Long-Context Software Engineering.
CoRR, November, 2025

GeoGNN: Quantifying and Mitigating Semantic Drift in Text-Attributed Graphs.
CoRR, November, 2025

Grounded Test-Time Adaptation for LLM Agents.
CoRR, November, 2025

ToolLibGen: Scalable Automatic Tool Creation and Aggregation for LLM Reasoning.
CoRR, October, 2025

CoDA: Coding LM via Diffusion Adaptation.
CoRR, October, 2025

LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software Engineering.
CoRR, September, 2025

UserBench: An Interactive Gym Environment for User-Centric Agents.
CoRR, July, 2025

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback.
CoRR, June, 2025

APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay.
CoRR, April, 2025

PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data.
CoRR, February, 2025

xLAM: A Family of Large Action Models to Empower AI Agent Systems.
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

ActionStudio: A Lightweight Framework for Data and Training of Large Action Models.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

LATTE: Learning to Think with Vision Specialists.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

SlackAgents: Scalable Collaboration of AI Agents in Workspaces.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

MCPEval: Automatic MCP-based Deep Evaluation for AI Agent Models.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit.
ACM Comput. Surv., December, 2024

Bridging the Data Provenance Gap Across Text, Speech and Video.
CoRR, 2024

TACO: Learning Multi-modal Action Models with Synthetic Chains-of-Thought-and-Action.
CoRR, 2024

SpecTool: A Benchmark for Characterizing Errors in Tool-Use LLMs.
CoRR, 2024

PRACT: Optimizing Principled Reasoning and Acting of LLM Agent.
CoRR, 2024

xLAM: A Family of Large Action Models to Empower AI Agent Systems.
CoRR, 2024

Consent in Crisis: The Rapid Decline of the AI Data Commons.
CoRR, 2024

APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets.
CoRR, 2024

MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases.
CoRR, 2024

AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System.
CoRR, 2024

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning.
CoRR, 2024


APIGen: Automated PIpeline for Generating Verifiable and Diverse Function-Calling Datasets.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

Personalized Multi-task Training for Recommender System.
Proceedings of the IEEE International Conference on Big Data, 2024

2023
DRDT: Dynamic Reflection with Divergent Thinking for LLM-based Sequential Recommendation.
CoRR, 2023

BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents.
CoRR, 2023

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization.
CoRR, 2023

Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System.
Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue, 2023

Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Zero-shot Item-based Recommendation via Multi-task Product Knowledge Graph Pre-Training.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Unsupervised Dense Retrieval Deserves Better Positive Pairs: Scalable Augmentation with Query Extraction and Generation.
CoRR, 2022

NaturalCC: An Open-Source Toolkit for Code Intelligence.
Proceedings of the 44th IEEE/ACM International Conference on Software Engineering: Companion Proceedings, 2022

Are Pre-trained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection.
Proceedings of the 4th Workshop on NLP for Conversational AI, 2022

2021
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection.
CoRR, 2021

Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation.
CoRR, 2021

Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Enriching Non-Autoregressive Transformer with Syntactic and Semantic Structures for Neural Machine Translation.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

2020
NaturalCC: A Toolkit to Naturalize the Source Code Corpus.
CoRR, 2020

MultiWOZ 2.2 : A Dialogue Dataset with Additional Annotation Corrections and State Tracking Baselines.
CoRR, 2020

Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking.
Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics, 2020

Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
Multi-Modal Generative Adversarial Network for Short Product Title Generation in Mobile E-Commerce.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

2018
Product Title Refinement via Multi-Modal Generative Adversarial Learning.
CoRR, 2018

Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction.
Proceedings of the IEEE International Conference on Data Mining, 2018


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