Papers
Toolformer: Language Models Can Teach Themselves to Use Tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessi et al.
ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings
Shibo Hao, Tianyang Liu, Zhen Wang et al.
ToolQA: A Dataset for LLM Question Answering with External Tools
Yuchen Zhuang, Yue Yu, Kuan Wang et al.
Tools for Verifying Neural Models' Training Data
Dami Choi, Yonadav Shavit, David K. Duvenaud
Top-Ambiguity Samples Matter: Understanding Why Deep Ensemble Works in Selective Classification
Qiang Ding, Yixuan Cao, Ping Luo
Topological Obstructions and How to Avoid Them
Babak Esmaeili, Robin Walters, Heiko Zimmermann et al.
Topological Parallax: A Geometric Specification for Deep Perception Models
Abraham Smith, Michael Catanzaro, Gabrielle Angeloro et al.
Topological RANSAC for instance verification and retrieval without fine-tuning
Guoyuan An, Ju-hyeong Seon, Inkyu An et al.
Topology-Aware Uncertainty for Image Segmentation
Saumya Gupta, Yikai Zhang, Xiaoling Hu et al.
TopoSRL: Topology preserving self-supervised Simplicial Representation Learning
Hiren Madhu, Sundeep Prabhakar Chepuri
TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models
Pum Jun Kim, Yoojin Jang, Jisu Kim et al.
To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis
Fuzhao Xue, Yao Fu, Wangchunshu Zhou et al.
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning
Ildus Sadrtdinov, Dmitrii Pozdeev, Dmitry P Vetrov et al.
Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms
Sijia Zhou, Yunwen Lei, Ata Kaban
Toward Re-Identifying Any Animal
Bingliang Jiao, Lingqiao Liu, Liying Gao et al.
Towards Accelerated Model Training via Bayesian Data Selection
Zhijie Deng, Peng Cui, Jun Zhu
Towards a Comprehensive Benchmark for High-Level Synthesis Targeted to FPGAs
Yunsheng Bai, Atefeh Sohrabizadeh, Zongyue Qin et al.
Towards a fuller understanding of neurons with Clustered Compositional Explanations
Biagio La Rosa, Leilani Gilpin, Roberto Capobianco
Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity
Metod Jazbec, James Allingham, Dan Zhang et al.
Towards A Richer 2D Understanding of Hands at Scale
Tianyi Cheng, Dandan Shan, Ayda Hassen et al.
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift
Xingdong Feng, Xin HE, Caixing Wang et al.
Towards a Unified Framework of Contrastive Learning for Disentangled Representations
Stefan Matthes, Zhiwei Han, Hao Shen
Towards Automated Circuit Discovery for Mechanistic Interpretability
Arthur Conmy, Augustine Mavor-Parker, Aengus Lynch et al.
Towards Better Dynamic Graph Learning: New Architecture and Unified Library
Le Yu, Leilei Sun, Bowen Du et al.
Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
Hedi Hadiji, Sarah Sachs, Tim van Erven et al.