11 citations · 11 across the 9 of their papers we have counts for
10 papers
A Combined Streaming FPGA Architecture for Client-Side CKKS Encoding and Encryption
Joseph Kurina, Bogdan Pasca, Suleyman Demirsoy +1
Homomorphic encryption allows a computing service to process encrypted data, but the client must first encode and encrypt its inputs. Sharing hardware between floating-point encodi…
Implicit Reasoning Steering via Concept Chaining
Xiao Ye, Sanika Chavan, Yuxi Huang +4
Large language models often appear to reason reliably, yet on many questions repeated sampling yields both correct and incorrect answers, revealing an underlying fragility in how f…
AFRILANGTUTOR: Advancing Language Tutoring and Culture Education in Low-Resource Languages with Large Language Models
Tadesse Destaw Belay, Shahriar Kabir Nahin, Israel Abebe Azime +6
How can language learning systems be developed for languages that lack sufficient training resources? This challenge is increasingly faced by developers across the African continen…
SafeLens: Deliberate and Efficient Video Guardrails with Fast-and-Slow Screening
Shahriar Kabir Nahin, Hadi Askari, Muhao Chen +1
The rapid growth of online video platforms and AI-generated content has made reliable video guardrails a key challenge for safety and real-world deployment. While most videos can b…
Revisiting the Effectiveness of LLM Pruning for Test-Time Scaling
Ocean Monjur, Shahriar Kabir Nahin, Anshuman Chhabra
Large Language Models (LLMs) now exhibit remarkable reasoning capabilities through test-time compute scaling (TTS), with impressive performance across math and coding benchmarks. I…
Retriv at BLP-2025 Task 2: Test-Driven Feedback-Guided Framework for Bangla-to-Python Code Generation
K M Nafi Asib, Sourav Saha, Mohammed Moshiul Hoque
Large Language Models (LLMs) have advanced the automated generation of code from natural language prompts. However, low-resource languages (LRLs) like Bangla remain underrepresente…
Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges
Anshuman Chhabra, Shrestha Datta, Shahriar Kabir Nahin +1
Agentic AI systems powered by large language models (LLMs) and endowed with planning, tool use, memory, and autonomy, are emerging as powerful, flexible platforms for automation. T…
Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models
Shahriar Kabir Nahin, Hadi Askari, Muhao Chen +1
Test-Time Scaling (TTS) improves LLM reasoning by exploring multiple candidate responses and then operating over this set to find the best output. A tacit premise behind TTS is tha…
What Is The Performance Ceiling of My Classifier? Utilizing Category-Wise Influence Functions for Pareto Frontier Analysis
Shahriar Kabir Nahin, Wenxiao Xiao, Joshua Liu +2
Data-centric learning seeks to improve model performance from the perspective of data quality, and has been drawing increasing attention in the machine learning community. Among it…
TituLLMs: A Family of Bangla LLMs with Comprehensive Benchmarking
Shahriar Kabir Nahin, Rabindra Nath Nandi, Sagor Sarker +7
In this paper, we present TituLLMs, the first large pretrained Bangla LLMs, available in 1b and 3b parameter sizes. Due to computational constraints during both training and infere…