Junjie Ye

Orcid: 0009-0004-0921-6323

According to our database1, Junjie Ye authored at least 38 papers between 2022 and 2025.

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

Timeline

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Bibliography

2025
Analyzing the Effects of Supervised Fine-Tuning on Model Knowledge from Token and Parameter Levels.
CoRR, September, 2025

AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning.
CoRR, September, 2025

Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments.
CoRR, August, 2025

VRPO: Rethinking Value Modeling for Robust RL Training under Noisy Supervision.
CoRR, August, 2025

SpeechRole: A Large-Scale Dataset and Benchmark for Evaluating Speech Role-Playing Agents.
CoRR, August, 2025

CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error Scenarios.
CoRR, June, 2025

Speech-Language Models with Decoupled Tokenizers and Multi-Token Prediction.
CoRR, June, 2025

A Multi-Dimensional Constraint Framework for Evaluating and Improving Instruction Following in Large Language Models.
CoRR, May, 2025

Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric.
CoRR, February, 2025

Predicting Large Language Model Capabilities on Closed-Book QA Tasks Using Only Information Available Prior to Training.
CoRR, February, 2025

Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training.
CoRR, January, 2025

ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

ToolHop: A Query-Driven Benchmark for Evaluating Large Language Models in Multi-Hop Tool Use.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Alleviating Shifted Distribution in Human Preference Alignment through Meta-Learning.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use.
CoRR, 2024

Empirical Insights on Fine-Tuning Large Language Models for Question-Answering.
CoRR, 2024

SafeAligner: Safety Alignment against Jailbreak Attacks via Response Disparity Guidance.
CoRR, 2024

MetaRM: Shifted Distributions Alignment via Meta-Learning.
CoRR, 2024

CodeChameleon: Personalized Encryption Framework for Jailbreaking Large Language Models.
CoRR, 2024

LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition.
CoRR, 2024

MouSi: Poly-Visual-Expert Vision-Language Models.
CoRR, 2024

Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback.
CoRR, 2024

ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios.
CoRR, 2024

Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

TransferTOD: A Generalizable Chinese Multi-Domain Task-Oriented Dialogue System with Transfer Capabilities.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

RoTBench: A Multi-Level Benchmark for Evaluating the Robustness of Large Language Models in Tool Learning.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Improving Discriminative Capability of Reward Models in RLHF Using Contrastive Learning.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

ToolSword: Unveiling Safety Issues of Large Language Models in Tool Learning Across Three Stages.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

LLM can Achieve Self-Regulation via Hyperparameter Aware Generation.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
RethinkingTMSC: An Empirical Study for Target-Oriented Multimodal Sentiment Classification.
CoRR, 2023

InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction.
CoRR, 2023

A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models.
CoRR, 2023

How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks.
CoRR, 2023

RethinkingTMSC: An Empirical Study for Target-Oriented Multimodal Sentiment Classification.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Sentiment-aware multimodal pre-training for multimodal sentiment analysis.
Knowl. Based Syst., 2022

Causal Intervention Improves Implicit Sentiment Analysis.
Proceedings of the 29th International Conference on Computational Linguistics, 2022


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