NeurIPS

Self-playing Adversarial Language Game Enhances LLM Reasoning

Pengyu Cheng, Tianhao Hu, Han Xu, Zhisong Zhang, Zheng Yuan, Yong Dai, Lei Han, Nan Du, Xiaolong Li

Comments Accepted by NeurIPS 2024

WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control

Claire Bizon Monroc, Ana Bušić, Donatien Dubuc, Jiamin Zhu

Journal ref 38th Conference on Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and Benchmarks

SubjECTive-QA: Measuring Subjectivity in Earnings Call Transcripts' QA Through Six-Dimensional Feature Analysis

Huzaifa Pardawala, Siddhant Sukhani, Agam Shah, Veer Kejriwal, Abhishek Pillai, Rohan Bhasin, Andrew DiBiasio, Tarun Mandapati, Dhruv Adha, Sudheer Chava

Comments Accepted at NeurIPS 2024

Beyond Task Diversity: Provable Representation Transfer for Sequential Multi-Task Linear Bandits

Thang Duong, Zhi Wang, Chicheng Zhang

Comments 38th Conference on Neural Information Processing Systems (NeurIPS 2024)

Fully Distributed, Flexible Compositional Visual Representations via Soft Tensor Products

Bethia Sun, Maurice Pagnucco, Yang Song

Comments Accepted to Neurips 2024. 10 pages + supplementary

Do's and Don'ts: Learning Desirable Skills with Instruction Videos

Hyunseung Kim, Byungkun Lee, Hojoon Lee, Dongyoon Hwang, Donghu Kim, Jaegul Choo

Comments published at NeurIPS 2024

Multi-Instance Partial-Label Learning with Margin Adjustment

Wei Tang, Yin-Fang Yang, Zhaofei Wang, Weijia Zhang, Min-Ling Zhang

Comments Accepted at NeurIPS 2024. The code can be found at https://github.com/tangw-seu/MIPLMA

Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior Models

Hui-Po Wang, Mario Fritz

Comments camera-ready in NeurIPS 2024

Counterfactual Fairness by Combining Factual and Counterfactual Predictions

Zeyu Zhou, Tianci Liu, Ruqi Bai, Jing Gao, Murat Kocaoglu, David I. Inouye

Comments In NeurIPS 2024

VisMin: Visual Minimal-Change Understanding

Rabiul Awal, Saba Ahmadi, Le Zhang, Aishwarya Agrawal

Comments Accepted at NeurIPS 2024. Project URL at https://vismin.net/

Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL

Qi Lv, Xiang Deng, Gongwei Chen, Michael Yu Wang, Liqiang Nie

Comments Accepted by NeurIPS 2024; Code is available at https://github.com/aopolin-lv/DecisionMamba

Journal ref The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024

Learning segmentation from point trajectories

Laurynas Karazija, Iro Laina, Christian Rupprecht, Andrea Vedaldi

Comments NeurIPS 2024 Spotlight. Project https://www.robots.ox.ac.uk/~vgg/research/lrtl/

$\spadesuit$ SPADE $\spadesuit$ Split Peak Attention DEcomposition

Malcolm Wolff, Kin G. Olivares, Boris Oreshkin, Sunny Ruan, Sitan Yang, Abhinav Katoch, Shankar Ramasubramanian, Youxin Zhang, Michael W. Mahoney, Dmitry Efimov, Vincent Quenneville-Bélair

Journal ref 31st Conference on Neural Information Processing In 38th Conference on Neural Information Processing Systems NIPS 2017, Time Series in the Age of Large Models Workshop, 2024

Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms

Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng

Comments Accepted to NeurIPS 2024

LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models

Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley, Otmar Hilliges, Romann M. Weber

Comments Published as a conference paper at NeurIPS 2024

Journal ref The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)

Can Bayesian Neural Networks Make Confident Predictions?

Katharine Fisher, Youssef Marzouk

Comments Mathematics of Modern Machine Learning Workshop at NeurIPS 2024

Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity

David Williams-King, Linh Le, Adam Oberman, Yoshua Bengio

Comments published at Neurips Safe Generative AI Workshop 2024

Certifying Robustness via Topological Representations

Jens Agerberg, Andrea Guidolin, Andrea Martinelli, Pepijn Roos Hoefgeest, David Eklund, Martina Scolamiero

Comments Workshop on Symmetry and Geometry in Neural Representations (NeurReps) at NeurIPS 2024, Extended Abstract Track

Bayesian Deconvolution of Astronomical Images with Diffusion Models: Quantifying Prior-Driven Features in Reconstructions

Alessio Spagnoletti, Alexandre Boucaud, Marc Huertas-Company, Wassim Kabalan, Biswajit Biswas

Comments 5+5 pages, 16 figures, Machine Learning and the Physical Sciences Workshop, NeurIPS 2024

Fair Secretaries with Unfair Predictions

Eric Balkanski, Will Ma, Andreas Maggiori

Comments NeurIPS 2024

From Transparent to Opaque: Rethinking Neural Implicit Surfaces with $α$-NeuS

Haoran Zhang, Junkai Deng, Xuhui Chen, Fei Hou, Wencheng Wang, Hong Qin, Chen Qian, Ying He

Comments NeurIPS 2024

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?

Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang, Fabian Isensee, Zifu Wang, Jieneng Chen, Yu-Cheng Chou, Yannick Kirchhoff, Maximilian Rokuss, Ziyan Huang, Jin Ye, Junjun He, Tassilo Wald, Constantin Ulrich, Michael Baumgartner, Saikat Roy, Klaus H. Maier-Hein, Paul Jaeger, Yiwen Ye, Yutong Xie, Jianpeng Zhang, Ziyang Chen, Yong Xia, Zhaohu Xing, Lei Zhu, Yousef Sadegheih, Afshin Bozorgpour, Pratibha Kumari, Reza Azad, Dorit Merhof, Pengcheng Shi, Ting Ma, Yuxin Du, Fan Bai, Tiejun Huang, Bo Zhao, Haonan Wang, Xiaomeng Li, Hanxue Gu, Haoyu Dong, Jichen Yang, Maciej A. Mazurowski, Saumya Gupta, Linshan Wu, Jiaxin Zhuang, Hao Chen, Holger Roth, Daguang Xu, Matthew B. Blaschko, Sergio Decherchi, Andrea Cavalli, Alan L. Yuille, Zongwei Zhou

Comments Accepted to NeurIPS-2024

On Improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models

Tariq Berrada Ifriqi, Pietro Astolfi, Melissa Hall, Reyhane Askari-Hemmat, Yohann Benchetrit, Marton Havasi, Matthew Muckley, Karteek Alahari, Adriana Romero-Soriano, Jakob Verbeek, Michal Drozdzal

Comments Accepted as a conference paper (poster) for NeurIPS 2024

Learning predictable and robust neural representations by straightening image sequences

Xueyan Niu, Cristina Savin, Eero P. Simoncelli

Comments Accepted at NeurIPS 2024

Assessing Bias in Metric Models for LLM Open-Ended Generation Bias Benchmarks

Nathaniel Demchak, Xin Guan, Zekun Wu, Ziyi Xu, Adriano Koshiyama, Emre Kazim

Comments NeurIPS 2024 EvalEval Workshop

Journal ref NeurIPS 2024 EvalEval Workshop

Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making

Manling Li, Shiyu Zhao, Qineng Wang, Kangrui Wang, Yu Zhou, Sanjana Srivastava, Cem Gokmen, Tony Lee, Li Erran Li, Ruohan Zhang, Weiyu Liu, Percy Liang, Li Fei-Fei, Jiayuan Mao, Jiajun Wu

Comments Accepted for oral presentation at NeurIPS 2024 in the Datasets and Benchmarks track. Final Camera version

Can Models Learn Skill Composition from Examples?

Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora

Comments Accepted to NeurIPS 2024

HEARTS: A Holistic Framework for Explainable, Sustainable and Robust Text Stereotype Detection

Theo King, Zekun Wu, Adriano Koshiyama, Emre Kazim, Philip Treleaven

Comments NeurIPS 2024 SoLaR Workshop and NeurIPS 2024 Safety Gen AI Workshop

Journal ref NeurIPS Safe Generative AI Workshop 2024; Workshop on Socially Responsible Language Modelling Research 2024

THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models

Mengfei Liang, Archish Arun, Zekun Wu, Cristian Munoz, Jonathan Lutch, Emre Kazim, Adriano Koshiyama, Philip Treleaven

Comments NeurIPS 2024 SoLaR (Socially Responsible Language Modelling Research ) Workshop

Journal ref NeurIPS Workshop on Socially Responsible Language Modelling Research 2024

Customizing Language Models with Instance-wise LoRA for Sequential Recommendation

Xiaoyu Kong, Jiancan Wu, An Zhang, Leheng Sheng, Hui Lin, Xiang Wang, Xiangnan He

Comments NeurIPS 2024 poster

Journal ref 38th Conference on Neural Information Processing Systems (NeurIPS 2024)