Ankit Singh Rawat
35 papers · 2015–2025 · 6 conferences · across top CS/AI conferences
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Conferences
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ICML (10)
NIPS (7)
AISTATS (3)
ACL (1)
EMNLP (1)
Top co-authors
Keywords
representation learning
(4)
neural network
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gradient descent
(3)
knowledge distillation
(3)
attention mechanism
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embedding dimension
(2)
large language model
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transformer architecture
(2)
information retrieval
(2)
nearest neighbor
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certified robustness
(1)
local learning
(1)
embedding learning
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natural language processing
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sparse recovery
(1)
federated learning
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embedding space
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bayesian inference
(1)
text generation
(1)
in-context learning
(1)
Papers
Faster Cascades via Speculative Decoding
ICLR 2025
Language Model Cascades: Token-Level Uncertainty And Beyond
ICLR 2024
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers
ICML 2024
A Statistical Framework for Data-dependent Retrieval-Augmented Models
ICML 2024
Dual-Encoders for Extreme Multi-label Classification
ICLR 2024
Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond
NIPS 2024
USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval
ICML 2024
DistillSpec: Improving Speculative Decoding via Knowledge Distillation
ICLR 2024
Think before you speak: Training Language Models With Pause Tokens
ICLR 2024
Analysis of Plan-based Retrieval for Grounded Text Generation
EMNLP 2024
Mechanics of Next Token Prediction with Self-Attention
AISTATS 2024
Teacher Guided Training: An Efficient Framework for Knowledge Transfer
ICLR 2023
Large Language Models with Controllable Working Memory
ACL 2023
Supervision Complexity and its Role in Knowledge Distillation
ICLR 2023
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
ICLR 2023
Serving Graph Compression for Graph Neural Networks
ICLR 2023
A Statistical Perspective on Retrieval-Based Models
ICML 2023
On the Role of Attention in Prompt-tuning
ICML 2023
In defense of dual-encoders for neural ranking
ICML 2022
RankDistil: Knowledge Distillation for Ranking
AISTATS 2021
Long-tail learning via logit adjustment
ICLR 2021
A statistical perspective on distillation
ICML 2021
Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces
ICML 2021
Overparameterisation and worst-case generalisation: friend or foe?
ICLR 2021
Federated Learning with Only Positive Labels
ICML 2020
Can gradient clipping mitigate label noise?
ICLR 2020
Are Transformers universal approximators of sequence-to-sequence functions?
ICLR 2020
Adversarial robustness via robust low rank representations
NIPS 2020
Robust large-margin learning in hyperbolic space
NIPS 2020
O(n) Connections are Expressive Enough: Universal Approximability of Sparse Transformers
NIPS 2020
Low-Rank Bottleneck in Multi-head Attention Models
ICML 2020
Multilabel reductions: what is my loss optimising?
NIPS 2019
Lifting high-dimensional non-linear models with Gaussian regressors
AISTATS 2019
Sampled Softmax with Random Fourier Features
NIPS 2019
Associative Memory via a Sparse Recovery Model
NIPS 2015