21 citations · 37 across the 29 of their papers we have counts for
10 papers · 1 filter
OVIBench: Benchmarking Online Video Question Answering under Interruption
Naiming Liu, Zhiheng Wu, Shuning Wang +3
Recent vision language models (VLMs) have achieved strong progress in video understanding. However, most existing video QA research and benchmarks still follow an offline, single-r…
See More, Think Deeper: Query-Expanded Visual Evidence and Answer-Clue Guided Reflection for Long Video Understanding
Shuning Wang, Zhiheng Wu, YiNuo Lu +6
Recent advances in Video Large Language Models (Video-LLMs) have enabled performance on long-video understanding tasks. However, existing methods still face two key limitations: ev…
MedHorizon: Towards Long-context Medical Video Understanding in the Wild
Bodong Du, Bowen Liu, Yang Yu +8
Medical multimodal large language models (MLLMs) have advanced image understanding and short-video analysis, but real clinical review often requires full-procedure video understand…
See Further, Think Deeper: Advancing VLM's Reasoning Ability with Low-level Visual Cues and Reflection
Zhiheng Wu, Tong Wang, Shuning Wang +2
Recent advances in Vision-Language Models (VLMs) have benefited from Reinforcement Learning (RL) for enhanced reasoning. However, existing methods still face critical limitations,…
Misconception Acquisition Dynamics in Large Language Models
Naiming Liu, Xinghe Chen, Richard Baraniuk +2
Effective educational AI depends on modeling student misconceptions. Such models enable realistic learner simulation and diagnostic, adaptive tutoring. However, instruction-tuning…
Circuit Complexity of Hierarchical Knowledge Tracing and Implications for Log-Precision Transformers
Naiming Liu, Richard Baraniuk, Shashank Sonkar
Knowledge tracing models mastery over interconnected concepts, often organized by prerequisites. We analyze hierarchical prerequisite propagation through a circuit-complexity lens…
MetaCLASS: Metacognitive Coaching for Learning with Adaptive Self-regulation Support
Naiming Liu, Richard Baraniuk, Shashank Sonkar
Large language models can generate fluent explanations, but effective tutoring requires supporting the learner's thought process, not just delivering content. Metacognitive tutorin…
Scalable Generation and Validation of Isomorphic Physics Problems with GenAI
Naiming Liu, Leo Murch, Spencer Moore +4
Traditional synchronous STEM assessments face growing challenges including accessibility barriers, security concerns from resource-sharing platforms, and limited comparability acro…
Learning Context: A Unified Framework and Roadmap for Context-Aware AI in Education
Naiming Liu, Brittany Bradford, Johaun Hatchett +5
We introduce a unified Learning Context (LC) framework designed to transition AI-based education from context-blind mimicry to a principled, holistic understanding of the learner.…
MalruleLib: Large-Scale Executable Misconception Reasoning with Step Traces for Modeling Student Thinking in Mathematics
Xinghe Chen, Naiming Liu, Shashank Sonkar
Student mistakes in mathematics are often systematic: a learner applies a coherent but wrong procedure and repeats it across contexts. We introduce MalruleLib, a learning-science-g…