3/ AgentIR: deep research agents explain what they're looking for before every search, and retrievers ignore all of it. We trained a retriever that reads that reasoning alongside the query, and search gets a lot better. arxiv.org/abs/2603.04384
Victor Zhong
Researcher with public evidence across AI business, AI research, NLP & language.
- AI signals
- 3 past 30d
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- Latest signal
- 17d ago
Articles & links
I helping recalibrate Waterloo’s software engineering program (and to some degree CS) for the age of AI. I wrote an essay on the challenges I’m seeing. www.victorzhong.com/writing/the-...
📣 I am hiring postdoctoral fellows in agentic AI at the R2L Lab @uwcheritoncs.bsky.social Lead your own agenda - systems that read, reason & act. Top-venue publishing, substantial compute, weekly PI 1:1s, and a real path to faculty/industry. Apply 👉 academicjobsonline.org/ajo/…
4/ We'll be at VLDB in Boston (Aug 31 - Sep 4) and COLM in San Francisco (Oct 5 - 17). If you want to talk retrieval, agents, or grounded QA, come say hi. It's been a busy half-year for the lab, w/ many new partnerships. We'll recruit 1-2 PhD students this September. Details a…
2/ LakeQuest: most QA benchmarks test on clean, well-organized text. Real data sits in messy data lakes full of tables, documents, and half-broken metadata. LakeQuest is a benchmark for answering questions there, with every answer traced back to its evidence. michael0402.githu…
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