FollowTable is the first large-scale benchmark for instruction-following table retrieval, paired with an Instruction Responsiveness Score, showing that existing models fail to adapt to fine-grained constraints beyond topical similarity.
InProceedings of the 34th ACM International Conference on Information and Knowledge Management(Seoul, Republic of Korea)(CIKM ’25)
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APG4RecSim automatically generates realistic user profiles for LLM-based recommendation simulations, outperforming manual baselines by up to 7% in nDCG@10 and 8% in JSD on three benchmark datasets.
PsyGAT structures conversations as dynamic temporal graphs with Psychological Expression Units and persona augmentation to reach state-of-the-art Macro F1 scores of 89.99 and 71.37 on DAIC-WoZ and E-DAIC while adding causal interpretability.
LLM-enhanced retrieval systems show large effectiveness gains on TREC benchmarks, yet adapted contamination checks indicate some gains may arise from memorization rather than methodological progress.
SID-Coord coordinates semantic IDs with hashed item IDs via attention fusion, adaptive gating, and interest alignment, yielding +0.664% long-play rate and +0.369% playback duration gains in production search ranking.
citing papers explorer
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FollowTable: A Benchmark for Instruction-Following Table Retrieval
FollowTable is the first large-scale benchmark for instruction-following table retrieval, paired with an Instruction Responsiveness Score, showing that existing models fail to adapt to fine-grained constraints beyond topical similarity.
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Task-Aware Automated User Profile Generation for Recommendation Simulation Using Large Language Models
APG4RecSim automatically generates realistic user profiles for LLM-based recommendation simulations, outperforming manual baselines by up to 7% in nDCG@10 and 8% in JSD on three benchmark datasets.
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Psychologically-Grounded Graph Modeling for Interpretable Depression Detection
PsyGAT structures conversations as dynamic temporal graphs with Psychological Expression Units and persona augmentation to reach state-of-the-art Macro F1 scores of 89.99 and 71.37 on DAIC-WoZ and E-DAIC while adding causal interpretability.
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The LLM Effect on IR Benchmarks: A Meta-Analysis of Effectiveness, Baselines, and Contamination
LLM-enhanced retrieval systems show large effectiveness gains on TREC benchmarks, yet adapted contamination checks indicate some gains may arise from memorization rather than methodological progress.
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SID-Coord: Coordinating Semantic IDs for ID-based Ranking in Short-Video Search
SID-Coord coordinates semantic IDs with hashed item IDs via attention fusion, adaptive gating, and interest alignment, yielding +0.664% long-play rate and +0.369% playback duration gains in production search ranking.