DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language Models (2024 · 20 citations)
LLMs such as GPT-4 score well on medical exam questions, but those benchmarks use short inputs and say little about whether a model's diagnostic reasoning can be inspected.
Query-Efficient Agentic Graph Extraction Attacks on GraphRAG Systems (2026 · 4 citations)
GraphRAG systems turn document collections into entity–relation knowledge graphs to support multi-hop reasoning.
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention (2026 · 1 citation)
Code language models usually learn where to "look" from token statistics alone. Human programmers instead concentrate on meaningful parts of code, such as conditions, signatures and data flow, and skim boilerplate. EyeMulator transfers this human selectivity into CodeLLMs without changing their architecture. The…
Graph-Assisted Large Language Models: A Perspective on Mitigating Intrinsic Limitations (2026)
This survey asks how graph structures can offset three built-in weaknesses of large language models. The first is knowledge: static training leads to outdated facts, errors, and unwanted memorization. The second is reasoning: token-by-token generation produces linear chains that cannot branch or backtrack. The third…

Co-authors here

12 of 18 co-authors with a page, the most papers together first.

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Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 13 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated 1 November 2026