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Dilshod Azizov

7 accepted papers

2026

CoTaP: Compliant Task Pipeline and Reinforcement Learning of Its Controller with Compliance Modulation

ICRA 2026poster

Humanoid whole-body locomotion control is a critical approach for humanoid robots to leverage their inherent advantages. Learning-based control methods derived from retargeted human motion data provide an effective means of addressing this issue. However, because most current human datasets lack mea…

2025

All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages

CVPR 2025highlight

Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cultural contexts, respect local sensitivities, and support low-resource languages, all while effectively integrating corr…

2025

CoDet-M4: Detecting Machine-Generated Code in Multi-Lingual, Multi-Generator and Multi-Domain Settings

ACL 2025finding

Large Language Models (LLMs) have revolutionized code generation, automating programming with remarkable efficiency. However, this has had important consequences for programming skills, ethics, and assessment integrity, thus making the detection of LLM-generated code essential for maintaining accoun…

Cited by 0SourcePDFScholar
2025

MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Media

NAACL 2025long

In the current era of rapidly growing digital data, evaluating the political bias and factuality of news outlets has become more important for seeking reliable information online. In this work, we study the classification problem of profiling news media from the lens of political bias and factuality…

2025

Profiling News Media for Factuality and Bias Using LLMs and the Fact-Checking Methodology of Human Experts

ACL 2025finding

In an age characterized by the proliferation of mis- and disinformation online, it is critical to empower readers to understand the content they are reading. Important efforts in this direction rely on manual or automatic fact-checking, which can be challenging for emerging claims with limited infor…

2024

Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation Distillation

AAAI 2024technical

Recently, because of the high-quality representations of contrastive learning methods, rehearsal-based contrastive continual learning has been proposed to explore how to continually learn transferable representation embeddings to avoid the catastrophic forgetting issue in traditional continual setti…

2024

SAFARI: Cross-lingual Bias and Factuality Detection in News Media and News Articles

EMNLP 2024finding

In an era where information is quickly shared across many cultural and language contexts, the neutrality and integrity of news media are essential. Ensuring that media content remains unbiased and factual is crucial for maintaining public trust. With this in mind, we introduce SAFARI (CroSs-lingual…

Cited by 3SourcePDFScholar