Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning | Paper Citation Record

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This paper cites Local computation of pagerank contributions.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Local computation of pagerank contributions

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This paper cites Transformers meet Neural Algorithmic Reasoners.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Transformers meet Neural Algorithmic Reasoners

Reference 2

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning GraphWiz: An Instruction-Following Language Model for Graph Problems

Reference 3

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Unresolved cited work

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This paper cites Talk like a Graph: Encoding Graphs for Large Language Models.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Talk like a Graph: Encoding Graphs for Large Language Models

Reference 5

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Computers and thought

Reference 6

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This paper cites Efficiently identifying task groupings for multi-task learning.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Efficiently identifying task groupings for multi-task learning

Reference 7

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning SIGN: Scalable Inception Graph Neural Networks

Reference 8

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This paper cites Beyond erdos-renyi: Generalization in algorithmic reasoning on graphs.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Beyond erdos-renyi: Generalization in algorithmic reasoning on graphs

Reference 9

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This paper cites Learning to branch for multi-task learning.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Learning to branch for multi-task learning

Reference 10

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This paper cites Dselect-k: Differentiable selection in the mixture of experts with applications to multi-task learning.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Dselect-k: Differentiable selection in the mixture of experts with applications to multi-task learning

Reference 11

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Lora: Low-rank adaptation of large language models

Reference 12

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This paper cites A generalist neural algorithmic learner.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning A generalist neural algorithmic learner

Reference 13

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Datamodels: Predicting predictions from training data

Reference 14

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This paper cites Neural tangent kernel: Convergence and generalization in neural networks.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Neural tangent kernel: Convergence and generalization in neural networks

Reference 15

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Extensions of Lipshitz mapping into Hilbert space

Reference 16

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This paper cites Heat kernel based community detection.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Heat kernel based community detection

Reference 17

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This paper cites Boosting multitask learning on graphs through higher-order task affinities.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Boosting multitask learning on graphs through higher-order task affinities

Reference 18

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This paper cites Identification of Negative Transfers in Multitask Learning Using Surrogate Models.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Identification of Negative Transfers in Multitask Learning Using Surrogate Models

Reference 19

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This paper cites Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity

Reference 20

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This paper cites Scalable Fine-tuning from Multiple Data Sources: A First-Order Approximation Approach.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Scalable Fine-tuning from Multiple Data Sources: A First-Order Approximation Approach

Reference 21

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This paper cites Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets

Reference 22

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This paper cites Topological structure of complex predictions.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Topological structure of complex predictions

Reference 23

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This paper cites Fully-adaptive feature sharing in multi-task networks with applications in person attribute classification.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Fully-adaptive feature sharing in multi-task networks with applications in person attribute classification

Reference 24

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Simulation of Graph Algorithms with Looped Transform- ers

Reference 25

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This paper cites Graphinstruct: Empowering large language models with graph understanding and reasoning capability.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Graphinstruct: Empowering large language models with graph understanding and reasoning capability

Reference 26

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This paper cites Modeling task relationships in multi-task learning with multi-gate mixture-of-experts.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Modeling task relationships in multi-task learning with multi-gate mixture-of-experts

Reference 27

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This paper cites The CLRS-Text Algorithmic Reasoning Language Benchmark.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning The CLRS-Text Algorithmic Reasoning Language Benchmark

Reference 28

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Towards Principled Graph Transformers

Reference 29

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Show Your Work: Scratchpads for Intermediate Computation with Language Models

Reference 30

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Trak: Attributing model behavior at scale

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Let Your Graph Do the Talking: Encoding Structured Data for LLMs

Reference 32

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning An Overview of Multi-Task Learning in Deep Neural Networks

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Artificial Intelligence: A modern approach

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Understanding transformer reasoning capabilities via graph algorithms

Reference 35

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Grapharena: Evaluating and exploring large lan- guage models on graph computation

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Graph neural prompting with large language models

Reference 37

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Fast random walk with restart and its applications

Reference 38

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Branched multi-task networks: Deciding what layers to share

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning The CLRS algorithmic reasoning benchmark

Reference 40

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Neural algorithmic reasoning

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Graph Attention Networks

Reference 42

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Neural execution of graph algorithms

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Iteratively Prompt Pre-trained Language Models for Chain of Thought

Reference 44

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Can Language Models Solve Graph Problems in Natural Language?

Reference 45

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Overlapping community detection using neighborhood-inflated seed expansion

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Understanding and improving information transfer in multi-task learning

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Precise high-dimensional asymptotics for quantifying heterogeneous transfers

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Overlapping community detection at scale: a nonnegative matrix factorization approach

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This paper cites Approximate personalized pagerank on dynamic graphs.

Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Approximate personalized pagerank on dynamic graphs

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Greaselm: Graph reasoning enhanced language models for question answering

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation

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Efficiently Learning Branching Networks for Multitask Algorithmic Reasoning We evaluate the error rates as one minus the average exact match across output text sequences

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