Papers
Compress to Impress: Unleashing the Potential of Compressive Memory in Real-World Long-Term Conversations
Nuo Chen, Hongguang Li, Jianhui Chang et al.
Compress to One Point: Neural Collapse for Pre-Trained Model-Based Class-Incremental Learning
Kun Wei, Zhe Xu, Cheng Deng
CompSlider: Compositional Slider for Disentangled Multiple-Attribute Image Generation
Zixin Zhu, Kevin Duarte, Mamshad Nayeem Rizve et al.
CompUGE-Bench: Comparative Understanding and Generation Evaluation Benchmark for Comparative Question Answering
Ahmad Shallouf, Irina Nikishina, Chris Biemann
Computable learning of natural hypothesis classes
Syed Akbari, Matthew Harrison-Trainor
Computational Analysis of Character Development in Holocaust Testimonies
Esther Shizgal, Eitan Wagner, Renana Keydar et al.
Computational Analysis of Conversation Dynamics through Participant Responsivity
Margaret Hughes, Brandon Roy, Elinor Poole-Dayan et al.
Computational Blueprints: Generating Isomorphic Mathematics Problems with Large Language Models
Jeong-Hoon Kim, Jinwoo Nam, Geunsik Jo
Computational Discovery of Chiasmus in Ancient Religious Text
Hope McGovern, Hale Sirin, Tom Lippincott
Computational Equivalence of Spiked Covariance and Spiked Wigner Models via Gram-Schmidt Perturbation
Guy Bresler, Alina Harbuzova
Computational Explorations of Total Variation Distance
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel et al.
Computational Intractability of Strategizing against Online Learners
Angelos Assos, Yuval Dagan, Nived Rajaraman
Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models
Jerry Yao-Chieh Hu, Maojiang Su, En-jui kuo et al.
Computationally Efficient Methods for Invariant Feature Selection with Sparsity
Jane Du, Arindam Banerjee
Computationally efficient reductions between some statistical models
Mengqi Lou, Guy Bresler, Ashwin Pananjady
Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics
Runzhe Wu, Ayush Sekhari, Akshay Krishnamurthy et al.
Computationally Hard Problems Are Hard for QBF Proof Systems Too
Agnes Schleitzer, Olaf Beyersdorff
Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification (extended abstract)
Dhruv Rohatgi, Adam Block, Audrey Huang et al.
Computational Story Lab at BLP-2025 Task 1: HateSense: A Multi-Task Learning Framework for Comprehensive Hate Speech Identification using LLMs
Tabia Tanzin Prama, Christopher M. Danforth, Peter Dodds
Computational Story Lab at BLP-2025 Task 1: HateSense: A Multi-Task Learning Framework for Comprehensive Hate Speech Identification using LLMs
Tabia Tanzin Prama, Christopher M. Danforth, Peter Dodds
Computation-Aware Kalman Filtering and Smoothing
Marvin Pförtner, Jonathan Wenger, Jon Cockayne et al.
Computation Mechanism Behind LLM Position Generalization
Chi Han, Heng Ji
Compute-Constrained Data Selection
Junjie Yin, Alexander M Rush