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09/08/2023
Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning
Real-world graphs naturally exhibit hierarchical or cyclical structures ...
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09/08/2023
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation
Pretraining molecular representations from large unlabeled data is essen...
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08/17/2023
Exploring Demonstration Ensembling for In-context Learning
In-context learning (ICL) operates by showing language models (LMs) exam...
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06/07/2023
When to Read Documents or QA History: On Unified and Selective Open-domain QA
This paper studies the problem of open-domain question answering, with t...
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05/24/2023
Discriminator-Guided Multi-step Reasoning with Language Models
In the context of multi-step reasoning, language models (LMs) probabilit...
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02/17/2023
Unsupervised Task Graph Generation from Instructional Video Transcripts
This work explores the problem of generating task graphs of real-world a...
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02/17/2023
Multimodal Subtask Graph Generation from Instructional Videos
Real-world tasks consist of multiple inter-dependent subtasks (e.g., a d...
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02/07/2023
Exploring the Benefits of Training Expert Language Models over Instruction Tuning
Recently, Language Models (LMs) instruction-tuned on multiple tasks, als...
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01/27/2023
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers
Since the recent advent of regulations for data protection (e.g., the Ge...
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01/07/2023
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching
Despite surprising performance on zero-shot transfer, pre-training a lar...
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10/27/2022
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost
To overcome the quadratic cost of self-attention, recent works have prop...
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10/04/2022
Knowledge Unlearning for Mitigating Privacy Risks in Language Models
Pretrained Language Models (LMs) memorize a vast amount of knowledge dur...
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09/07/2022
Grouping-matrix based Graph Pooling with Adaptive Number of Clusters
Graph pooling is a crucial operation for encoding hierarchical structure...
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08/11/2022
Symbolic Music Loop Generation with Neural Discrete Representations
Since most of music has repetitive structures from motifs to phrases, re...
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07/06/2022
Pure Transformers are Powerful Graph Learners
We show that standard Transformers without graph-specific modifications ...
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06/16/2022
Is Continual Learning Truly Learning Representations Continually?
Continual learning (CL) aims to learn from sequentially arriving tasks w...
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05/28/2022
Few-shot Subgoal Planning with Language Models
Pre-trained large language models have shown successful progress in many...
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05/25/2022
LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA
We study unsupervised multi-hop reranking for multi-hop QA (MQA) with op...
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01/29/2022
Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning
Batch Normalization (BN) is an essential layer for training neural netwo...
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11/12/2021
On-the-Fly Rectification for Robust Large-Vocabulary Topic Inference
Across many data domains, co-occurrence statistics about the joint appea...
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11/19/2017
Prior-aware Dual Decomposition: Document-specific Topic Inference for Spectral Topic Models
Spectral topic modeling algorithms operate on matrices/tensors of word c...
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11/18/2017
Low-dimensional Embeddings for Interpretable Anchor-based Topic Inference
The anchor words algorithm performs provably efficient topic model infer...
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11/01/2016
Robust Spectral Inference for Joint Stochastic Matrix Factorization
Spectral inference provides fast algorithms and provable optimality for ...
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01/12/2016
Basic Reasoning with Tensor Product Representations
In this paper we present the initial development of a general theory for...
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11/19/2015
