Kening Zheng

According to our database1, Kening Zheng authored at least 15 papers between 2024 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness.
CoRR, May, 2026

ARC-STAR: Auditable Post-Hoc Correction for PDE Foundation Models.
CoRR, May, 2026

Towards Robust LLM Post-Training: Automatic Failure Management for Reinforcement Fine-Tuning.
CoRR, May, 2026

Unveiling Language Routing Isolation in Multilingual MoE Models for Interpretable Subnetwork Adaptation.
CoRR, April, 2026

CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification.
CoRR, April, 2026

When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation.
CoRR, April, 2026

Unlocking Multimodal Document Intelligence: From Current Triumphs to Future Frontiers of Visual Document Retrieval.
CoRR, February, 2026

2025
GM-PRM: A Generative Multimodal Process Reward Model for Multimodal Mathematical Reasoning.
CoRR, August, 2025

Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

SafeEraser: Enhancing Safety in Multimodal Large Language Models through Multimodal Machine Unlearning.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models.
CoRR, 2024

Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models.
CoRR, 2024

Refiner: Restructure Retrieval Content Efficiently to Advance Question-Answering Capabilities.
CoRR, 2024

Refiner: Restructure Retrieved Content Efficiently to Advance Question-Answering Capabilities.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024


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