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cs.IR2026
Towards Critical IR Theories and Practices
Bhaskar Mitra
Belkin and Robertson urged us, half a century ago, to develop a theoretical foundation for understanding what constitutes societal good that can inform information retrieval (IR) r…
cs.IR2026
From Noise to Order: Learning to Rank via Denoising Diffusion
Sajad Ebrahimi, Bhaskar Mitra, Negar Arabzadeh +4
In information retrieval (IR), learning-to-rank (LTR) methods have traditionally limited themselves to discriminative machine learning approaches that model the probability of the…
cs.CL2026
PolyAlign: Conditional Human-Distribution Alignment
L. D. M. S. Sai Teja, Ufaq Khan, Sathira Silva +2
Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective fo…