4 citations · 5 across the 11 of their papers we have counts for
11 papers
SymStep: Symbolic Step Verification for Logical Reasoning
Aida Usmanova, Rui Gao, Dilshod Azizov +2
Chain-of-thought (CoT) prompting can fail severely on constraint-dense logical reasoning tasks, where unverified errors accumulate silently across steps. We introduce SymStep: an L…
A Multi-View Media Profiling Suite: Resources, Evaluation, and Analysis
Muhammad Arslan Manzoor, Dilshod Azizov, Daniil Orel +4
News outlets shape public opinion at a scale that makes automated detection of political bias and factuality essential. However, the field still lacks unified resources, comprehens…
AICD Bench: A Challenging Benchmark for AI-Generated Code Detection
Daniil Orel, Dilshod Azizov, Indraneil Paul +3
Large language models (LLMs) are increasingly capable of generating functional source code, raising concerns about authorship, accountability, and security. While detecting AI-gene…
CoTaP: Compliant Task Pipeline and Reinforcement Learning of Its Controller with Compliance Modulation
Zewen He, Chenyuan Chen, Dilshod Azizov +1
Humanoid whole-body locomotion control is a critical approach for humanoid robots to leverage their inherent advantages. Learning-based control methods derived from retargeted huma…
Profiling News Media for Factuality and Bias Using LLMs and the Fact-Checking Methodology of Human Experts
Zain Muhammad Mujahid, Dilshod Azizov, Maha Tufail Agro +1
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 t…
Evolution of AI in Education: Agentic Workflows
Firuz Kamalov, David Santandreu Calonge, Linda Smail +4
The primary goal of this study is to analyze agentic workflows in education according to the proposed four major technological paradigms: reflection, planning, tool use, and multi-…
CoDet-M4: Detecting Machine-Generated Code in Multi-Lingual, Multi-Generator and Multi-Domain Settings
Daniil Orel, Dilshod Azizov, Preslav Nakov
Large language models (LLMs) have revolutionized code generation, automating programming with remarkable efficiency. However, these advancements challenge programming skills, ethic…
A Decade of Deep Learning: A Survey on The Magnificent Seven
Dilshod Azizov, Muhammad Arslan Manzoor, Velibor Bojkovic +9
Deep learning has fundamentally reshaped the landscape of artificial intelligence over the past decade, enabling remarkable achievements across diverse domains. At the heart of the…
MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Media
Muhammad Arslan Manzoor, Ruihong Zeng, Dilshod Azizov +2
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.…
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages
Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66
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 cul…
Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation Distillation
Jiyong Li, Dilshod Azizov, Yang Li +1
Recently, because of the high-quality representations of contrastive learning methods, rehearsal-based contrastive continual learning has been proposed to explore how to continuall…