10 papers
A Vision Toward Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents
Abhijit Chatterjee, Niraj K. Jha, Jonathan D. Cohen +6
The field of artificial intelligence (AI) has taken a tight hold on broad aspects of society, industry, business, and governance in ways that dictate the prosperity and might of th…
LinMU: Multimodal Understanding Made Linear
Hongjie Wang, Niraj K. Jha
Modern Vision-Language Models (VLMs) achieve impressive performance but are limited by the quadratic complexity of self-attention, which prevents their deployment on edge devices a…
Knowledge Graphs are Implicit Reward Models: Path-Derived Signals Enable Compositional Reasoning
Yuval Kansal, Niraj K. Jha
Large language models have achieved near-expert performance in structured reasoning domains like mathematics and programming, yet their ability to perform compositional multi-hop r…
CD4LM: Consistency Distillation and aDaptive Decoding for Diffusion Language Models
Yihao Liang, Ze Wang, Hao Chen +7
Autoregressive large language models achieve strong results on many benchmarks, but decoding remains fundamentally latency-limited by sequential dependence on previously generated…
Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Need
Bhishma Dedhia, Yuval Kansal, Niraj K. Jha
Language models traditionally used for cross-domain generalization have recently demonstrated task-specific reasoning. However, their top-down training approach on general corpora…
Learning Interpretable Differentiable Logic Networks for Time-Series Classification
Chang Yue, Niraj K. Jha
Differentiable logic networks (DLNs) have shown promising results in tabular domains by combining accuracy, interpretability, and computational efficiency. In this work, we apply D…