Papers
Scaling Inference-Efficient Language Models
Song Bian, Minghao Yan, Shivaram Venkataraman
IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck
Tian Bian, Yifan Niu, Chaohao Yuan et al.
Rethinking Point Cloud Data Augmentation: Topologically Consistent Deformation
Jian Bi, Qianliang Wu, Xiang Li et al.
Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning
Zhenni Bi, Kai Han, Chuanjian Liu et al.
Learning multivariate Gaussians with imperfect advice
Arnab Bhattacharyya, Davin Choo, Philips George John et al.
Almost Optimal Fully Dynamic k-Center Clustering with Recourse
Sayan Bhattacharya, Martin Costa, Ermiya Farokhnejad et al.
Multi-Objective Causal Bayesian Optimization
Shriya Bhatija, Paul-David Zuercher, Jakob Thumm et al.
AtlasD: Automatic Local Symmetry Discovery
Manu Bhat, Jonghyun Park, Jianke Yang et al.
Multiaccuracy and Multicalibration via Proxy Groups
Beepul Bharti, Mary Versa Clemens-Sewall, Paul Yi et al.
Auto-reconfiguration for Latency Minimization in CPU-based DNN Serving
Ankit Bhardwaj, Amar Phanishayee, Deepak Narayanan et al.
Highly Compressed Tokenizer Can Generate Without Training
Lukas Lao Beyer, Tianhong Li, Xinlei Chen et al.
Whitened CLIP as a Likelihood Surrogate of Images and Captions
Roy Betser, Meir Yossef Levi, Guy Gilboa
Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs
Jan Betley, Daniel Chee Hian Tan, Niels Warncke et al.
Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection
Louis Béthune, David Grangier, Dan Busbridge et al.
Near-optimal Sketchy Natural Gradients for Physics-Informed Neural Networks
Maricela Best Mckay, Avleen Kaur, Chen Greif et al.
Geometry-Informed Neural Networks
Arturs Berzins, Andreas Radler, Eric Volkmann et al.
Self-Play Q-Learners Can Provably Collude in the Iterated Prisoner’s Dilemma
Quentin Bertrand, Juan Agustin Duque, Emilio Calvano et al.
Differential Privacy Guarantees of Markov Chain Monte Carlo Algorithms
Andrea Bertazzi, Tim Johnston, Gareth O. Roberts et al.
Modular Duality in Deep Learning
Jeremy Bernstein, Laker Newhouse
Online Learning in the Random-Order Model
Martino Bernasconi, Andrea Celli, Riccardo Colini Baldeschi et al.
No-Regret is not enough! Bandits with General Constraints through Adaptive Regret Minimization
Martino Bernasconi, Matteo Castiglioni, Andrea Celli
Global curvature for second-order optimization of neural networks
Alberto Bernacchia
Memory Layers at Scale
Vincent-Pierre Berges, Barlas Oguz, Daniel Haziza et al.
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs
Akhiad Bercovich, Tomer Ronen, Talor Abramovich et al.
Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search
Ziyad Benomar, Lorenzo Croissant, Vianney Perchet et al.