ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios.
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Proceedings of the 31st International Conference on Computational Linguistics, 2025
Are Your LLMs Capable of Stable Reasoning?
CoRR, 2024
AgentGym: Evolving Large Language Model-based Agents across Diverse Environments.
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CoRR, 2024
Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model.
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CoRR, 2024
The Fine Line: Navigating Large Language Model Pretraining with Down-streaming Capability Analysis.
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CoRR, 2024
EasyJailbreak: A Unified Framework for Jailbreaking Large Language Models.
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CoRR, 2024
Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback.
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CoRR, 2024
Secrets of RLHF in Large Language Models Part II: Reward Modeling.
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CoRR, 2024
ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios.
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CoRR, 2024
CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing.
Proceedings of the Natural Language Processing and Chinese Computing, 2024
Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback.
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Proceedings of the Forty-first International Conference on Machine Learning, 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
Inverse-Q*: Token Level Reinforcement Learning for Aligning Large Language Models Without Preference Data.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 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
Navigating the OverKill in Large Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin.
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Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
LoRAMoE: Revolutionizing Mixture of Experts for Maintaining World Knowledge in Language Model Alignment.
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CoRR, 2023
TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models.
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CoRR, 2023
Echotune: A Modular Extractor Leveraging the Variable-Length Nature of Speech in ASR Tasks.
CoRR, 2023
Self-Polish: Enhance Reasoning in Large Language Models via Problem Refinement.
CoRR, 2023
CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing.
CoRR, 2023
RealBehavior: A Framework for Faithfully Characterizing Foundation Models' Human-like Behavior Mechanisms.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Self-Polish: Enhance Reasoning in Large Language Models via Problem Refinement.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Farewell to Aimless Large-scale Pretraining: Influential Subset Selection for Language Model.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature Perspective.
CoRR, 2022
Kernel-Whitening: Overcome Dataset Bias with Isotropic Sentence Embedding.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature Perspective.
Proceedings of the 29th International Conference on Computational Linguistics, 2022