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45%Niche pick
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Contrastive Retrieval Heads for Improved Attention-Based Reranking

Linh Tran, Yulong Li, Radu Florian, Stacy Patterson and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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0/20 AI panelreviewers recommend it

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AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
74%Highly rated
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RVR: Retrieve-Verify-Retrieve for Comprehensive Question Answering

RVR uses retrieve-verify-retrieve loops with verified documents to augment queries, improving multi-answer recall by at least 10% relative over baselines.

Deniz Qian, Hung-Ting Chen, Eunsol Choi

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 4/5
medium 4/10
strict 1/5
88%Must read
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Hi-Q: Hierarchical Evidence-guided Query Refinement for Multi-Hop Question Answering

Hi-Q hierarchically refines multi-hop queries via evidence-guided resolution and expansion, outperforming iterative and graph-based retrieval baselines on full-corpus benchmarks.

Jueun Kim, Sungho Park, WOOK SHIN HAN

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 35 on Hugging Face · Code ★ 1

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 3/5