:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Ying, Qiao, Congyu, Geng, Xin, Xu, Ning
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2605.07883
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Progressively Label Enhancement for Large Language Model Alignment
by: Liu, Biao, et al.
Published: (2024)

Reduction-based Pseudo-label Generation for Instance-dependent Partial Label Learning
by: Qiao, Congyu, et al.
Published: (2024)

Beyond Rejection Sampling: Trajectory Fusion for Scaling Mathematical Reasoning
by: Deng, Jie, et al.
Published: (2026)

Negative-Prompt-driven Alignment for Generative Language Model
by: Qiao, Shiqi, et al.
Published: (2024)

Alignment through Meta-Weighted Online Sampling: Bridging the Gap between Data Generation and Preference Optimization
by: Yang, Junming, et al.
Published: (2025)

Beyond Performance: Quantifying and Mitigating Label Bias in LLMs
by: Reif, Yuval, et al.
Published: (2024)

FalseReject: A Resource for Improving Contextual Safety and Mitigating Over-Refusals in LLMs via Structured Reasoning
by: Zhang, Zhehao, et al.
Published: (2025)

Rejection Improves Reliability: Training LLMs to Refuse Unknown Questions Using RL from Knowledge Feedback
by: Xu, Hongshen, et al.
Published: (2024)

LLMs cannot spot math errors, even when allowed to peek into the solution
by: Srivatsa, KV Aditya, et al.
Published: (2025)

VRM: Teaching Reward Models to Understand Authentic Human Preferences
by: Liu, Biao, et al.
Published: (2026)

Enhancing RAG with Active Learning on Conversation Records: Reject Incapables and Answer Capables
by: Geng, Xuzhao, et al.
Published: (2025)

Reasons to Reject? Aligning Language Models with Judgments
by: Xu, Weiwen, et al.
Published: (2023)

LLMs Struggle to Reject False Presuppositions when Misinformation Stakes are High
by: Sieker, Judith, et al.
Published: (2025)

Preference Orchestrator: Prompt-Aware Multi-Objective Alignment for Large Language Models
by: Liu, Biao, et al.
Published: (2025)

Fast Best-of-N Decoding via Speculative Rejection
by: Sun, Hanshi, et al.
Published: (2024)

Beyond the Score: Uncertainty-Calibrated LLMs for Automated Essay Assessment
by: Karim, Ahmed, et al.
Published: (2025)

CrossTune: Black-Box Few-Shot Classification with Label Enhancement
by: Luo, Danqing, et al.
Published: (2024)

LLMs cannot find reasoning errors, but can correct them given the error location
by: Tyen, Gladys, et al.
Published: (2023)

Diagnosing and Remedying Knowledge Deficiencies in LLMs via Label-free Curricular Meaningful Learning
by: Xiong, Kai, et al.
Published: (2024)

Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future
by: Wang, Yidong, et al.
Published: (2025)

ING-VP: MLLMs cannot Play Easy Vision-based Games Yet
by: Zhang, Haoran, et al.
Published: (2024)

General LLMs as Instructors for Domain-Specific LLMs: A Sequential Fusion Method to Integrate Extraction and Editing
by: Zhang, Xin, et al.
Published: (2024)

Alleviating Distribution Shift in Synthetic Data for Machine Translation Quality Estimation
by: Geng, Xiang, et al.
Published: (2025)

Show or Tell? Modeling the evolution of request-making in Human-LLM conversations
by: Zhu, Shengqi, et al.
Published: (2025)

Beyond Binary Gender Labels: Revealing Gender Biases in LLMs through Gender-Neutral Name Predictions
by: You, Zhiwen, et al.
Published: (2024)

Referential ambiguity and clarification requests: comparing human and LLM behaviour
by: Madge, Chris, et al.
Published: (2025)

Jailbreaking LLMs via Semantically Relevant Nested Scenarios with Targeted Toxic Knowledge
by: Xu, Ning, et al.
Published: (2025)

Augmenting In-Context-Learning in LLMs via Automatic Data Labeling and Refinement
by: Shtok, Joseph, et al.
Published: (2024)

Aligning Reasoning LLMs for Materials Discovery with Physics-aware Rejection Sampling
by: Hyun, Lee, et al.
Published: (2025)

Beyond Single-Task: Robust Multi-Task Length Generalization for LLMs
by: Hu, Yi, et al.
Published: (2025)

What I cannot execute, I do not understand: Training and Evaluating LLMs on Program Execution Traces
by: Armengol-Estapé, Jordi, et al.
Published: (2025)

LLMs Can Also Do Well! Breaking Barriers in Semantic Role Labeling via Large Language Models
by: Li, Xinxin, et al.
Published: (2025)

Beyond Surface Statistics: Robust Conformal Prediction for LLMs via Internal Representations
by: Wang, Yanli, et al.
Published: (2026)

Beyond GPT-5: Making LLMs Cheaper and Better via Performance-Efficiency Optimized Routing
by: Zhang, Yiqun, et al.
Published: (2025)

Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection
by: Hu, Shuguo, et al.
Published: (2025)

Large Language Model probabilities cannot distinguish between possible and impossible language
by: Leivada, Evelina, et al.
Published: (2025)

Current LLMs still cannot 'talk much' about grammar modules: Evidence from syntax
by: Shormani, Mohammed Q., et al.
Published: (2026)

Unveiling the Lexical Sensitivity of LLMs: Combinatorial Optimization for Prompt Enhancement
by: Zhan, Pengwei, et al.
Published: (2024)

How to Alleviate Catastrophic Forgetting in LLMs Finetuning? Hierarchical Layer-Wise and Element-Wise Regularization
by: Song, Shezheng, et al.
Published: (2025)

WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning
by: Yu, Zhaojian, et al.
Published: (2023)