From the 1 of 9 linked papers with an AI index.
9 papers
Implicit Reasoning Steering via Concept Chaining
Xiao Ye, Sanika Chavan, Yuxi Huang +4
The paper introduces Concept Chaining, a method that creates short natural-language paragraphs linking question entities to a target answer via intermediate concepts, and uses cont…
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…
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…
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…
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…