Sparse GNN training reduces computation, but deciding which edges to keep can be costly. Reusing one sparse graph is cheap, but locks training to a fixed topology, while varying it across epochs can require repeated sampling or recomputation. We introduce EDiS (Edge-Disjoint Subgraph sparsification framework), which se...
S. Navuluru, Siddhartha Shankar Das, Franck Dernoncourt et al.· 0 citations
Skills are external artifacts that Large Language Models (LLMs) consume at inference time to improve their performance on specialized domains by incorporating relevant procedural and domain knowledge. Expert-authored skills are expensive to produce, and the resulting artifacts are not optimized for the specific model t...
To the authors' knowledge, Scaffold is the first scalable GNN sparsification framework to use a joint supporting-path dilation-congestion criterion, and across 19 homophilic and heterophilic benchmarks, Scaffold achieves the best aggregate rank among the evaluated sparsification and related methods.
Siddhartha Shankar Das, S. Navuluru, S. M. Ferdous et al.· 0 citations
GRS-QA is introduced, a reasoning graph-structured question answering dataset that augments multi-hop QA instances from exisiting datasets, with directed reasoning graphs representing intermediate inference steps, and highlights the importance of unified structural annotations for understanding and improving multi-hop...
Khin S. Yone, Devasha Trivedi, Anish Pahilajani et al.· International Conference on...· 0 citations
A common layer equation is introduced that represents covered architectures through seven components: an update domain, channel set, propagation bank, per-channel message maps, channel-fusion operator, ego/residual map, and update map, which exposes the empirical inverse problem of mapping measurable graph and task pro...
S. Navuluru, Siddhartha Shankar Das, B. Ni et al.· 0 citations
This work introduces the problem of personalized auto-research, which conditions every stage of the research process on a representation of the individual researcher, and proposes a general and flexible framework that threads a graph-grounded researcher context through retrieval, hypothesis search, experimentation, wri...
B. Ni, Franck Dernoncourt, Hong-Jie Chen et al.· 0 citations
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