11 citations · 37 across the 35 of their papers we have counts for
23 papers · 1 filter
GUI-Primitives: Diagnosing Spatial Reasoning Failures in Vision-Language GUI Grounding
Md Abrar Jahin, Md Rizwan Parvez
Computer-use agents ground natural-language instructions in screenshots to locate interface elements, yet existing benchmarks do not isolate whether models bind relational language…
Self-Consistency from Only Two Samples: CoT-PoT Ensembling for Efficient LLM Reasoning
Raman Saparkhan, Majd Hawasly, Md Rizwan Parvez +1
Self-consistency (SC) is a popular technique for improving the reasoning accuracy of large language models by aggregating multiple sampled outputs, but it comes at a high computati…
A Survey on Agentic Security: Applications, Threats and Defenses
Asif Shahriar, Md Nafiu Rahman, Sadif Ahmed +2
LLM-based agents are now used throughout cybersecurity. While these agents facilitate powerful and autonomous security applications, their autonomy opens up new attack surfaces, an…
DashboardQA: Benchmarking Multimodal Agents for Question Answering on Interactive Dashboards
Aaryaman Kartha, Ahmed Masry, Mohammed Saidul Islam +8
Dashboards are powerful visualization tools for data-driven decision-making, integrating multiple interactive views that allow users to explore, filter, and navigate data. Unlike s…
Xolver: Multi-Agent Reasoning with Holistic Experience Learning Just Like an Olympiad Team
Md Tanzib Hosain, Salman Rahman, Md Kishor Morol +1
Despite impressive progress on complex reasoning, current large language models (LLMs) typically operate in isolation - treating each problem as an independent attempt, without acc…
AI Debate Aids Assessment of Controversial Claims
Salman Rahman, Sheriff Issaka, Ashima Suvarna +11
As AI grows more powerful, it will increasingly shape how we understand the world. But with this influence comes the risk of amplifying misinformation and deepening social divides-…
ChartQAPro: A More Diverse and Challenging Benchmark for Chart Question Answering
Ahmed Masry, Mohammed Saidul Islam, Mahir Ahmed +11
Charts are ubiquitous, as people often use them to analyze data, answer questions, and discover critical insights. However, performing complex analytical tasks with charts requires…
CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging
Md. Ashraful Islam, Mohammed Eunus Ali, Md Rizwan Parvez
Large Language Models (LLMs) have made significant strides in code generation and problem solving. Current approaches employ external tool-based iterative debuggers that use compil…
MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models
Mahir Labib Dihan, Md Tanvir Hassan, Md Tanvir Parvez +5
Recent advancements in foundation models have improved autonomous tool usage and reasoning, but their capabilities in map-based reasoning remain underexplored. To address this, we…
MapQaTor: An Extensible Framework for Efficient Annotation of Map-Based QA Datasets
Mahir Labib Dihan, Mohammed Eunus Ali, Md Rizwan Parvez
Mapping and navigation services like Google Maps, Apple Maps, OpenStreetMap, are essential for accessing various location-based data, yet they often struggle to handle natural lang…
Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models
Shayekh Bin Islam, Md Asib Rahman, K S M Tozammel Hossain +3
Retrieval-Augmented Generation (RAG) has been shown to enhance the factual accuracy of Large Language Models (LLMs), but existing methods often suffer from limited reasoning capabi…
DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts
Mohammed Saidul Islam, Md Tahmid Rahman Laskar, Md Rizwan Parvez +2
Data-driven storytelling is a powerful method for conveying insights by combining narrative techniques with visualizations and text. These stories integrate visual aids, such as hi…
A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations
Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari +10
Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough…
MapCoder: Multi-Agent Code Generation for Competitive Problem Solving
Md. Ashraful Islam, Mohammed Eunus Ali, Md Rizwan Parvez
Code synthesis, which requires a deep understanding of complex natural language problem descriptions, generation of code instructions for complex algorithms and data structures, an…
Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis
Sabri Boughorbel, MD Rizwan Parvez, Majd Hawasly
Training LLMs for low-resource languages usually utilizes data augmentation from English using machine translation (MT). This, however, brings a number of challenges to LLM trainin…
ChartInstruct: Instruction Tuning for Chart Comprehension and Reasoning
Ahmed Masry, Mehrad Shahmohammadi, Md Rizwan Parvez +2
Charts provide visual representations of data and are widely used for analyzing information, addressing queries, and conveying insights to others. Various chart-related downstream…
Chain of Evidences and Evidence to Generate: Prompting for Context Grounded and Retrieval Augmented Reasoning
Md Rizwan Parvez
While chain-of-thoughts (CoT) prompting has revolutionized how LLMs perform reasoning tasks, its current methods and variations (e.g, Self-consistency, ReACT, Reflexion, Tree-of-Th…
DelucionQA: Detecting Hallucinations in Domain-specific Question Answering
Mobashir Sadat, Zhengyu Zhou, Lukas Lange +6
Hallucination is a well-known phenomenon in text generated by large language models (LLMs). The existence of hallucinatory responses is found in almost all application scenarios e.…
Learning to Filter Context for Retrieval-Augmented Generation
Zhiruo Wang, Jun Araki, Zhengbao Jiang +2
On-the-fly retrieval of relevant knowledge has proven an essential element of reliable systems for tasks such as open-domain question answering and fact verification. However, beca…
xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval
Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do +3
Recently, pre-trained large language models (LLMs) have shown impressive abilities in generating codes from natural language descriptions, repairing buggy codes, translating codes…
Retrieval Enhanced Data Augmentation for Question Answering on Privacy Policies
Md Rizwan Parvez, Jianfeng Chi, Wasi Uddin Ahmad +2
Prior studies in privacy policies frame the question answering (QA) task as identifying the most relevant text segment or a list of sentences from a policy document given a user qu…
Evaluating the Values of Sources in Transfer Learning
Md Rizwan Parvez, Kai-Wei Chang
Transfer learning that adapts a model trained on data-rich sources to low-resource targets has been widely applied in natural language processing (NLP). However, when training a tr…
Building Language Models for Text with Named Entities
Md Rizwan Parvez, Saikat Chakraborty, Baishakhi Ray +1
Text in many domains involves a significant amount of named entities. Predict- ing the entity names is often challenging for a language model as they appear less frequent on the tr…