Search Results for author: Sanchit Sinha

Found 10 papers, 4 papers with code

Leveraging Scale-aware Representations for improved Concept-Representation Alignment in ViTs

no code implementations16 Jan 2025 Sanchit Sinha, Guangzhi Xiong, Aidong Zhang

Vision Transformers (ViTs) are increasingly being adopted in various sensitive vision applications - like medical diagnosis, facial recognition, etc.

Medical Diagnosis

Structural Causality-based Generalizable Concept Discovery Models

no code implementations20 Oct 2024 Sanchit Sinha, Guangzhi Xiong, Aidong Zhang

Our method assumes generative factors and concepts to form a bipartite graph, with directed causal edges from generative factors to concepts.

Disentanglement

ProtoNAM: Prototypical Neural Additive Models for Interpretable Deep Tabular Learning

1 code implementation7 Oct 2024 Guangzhi Xiong, Sanchit Sinha, Aidong Zhang

In this work, we propose a new deep tabular learning method, termed Prototypical Neural Additive Model (ProtoNAM), which introduces prototypes into neural networks in the framework of GAMs.

Additive models

CoLiDR: Concept Learning using Aggregated Disentangled Representations

no code implementations27 Jul 2024 Sanchit Sinha, Guangzhi Xiong, Aidong Zhang

Interpretability of Deep Neural Networks using concept-based models offers a promising way to explain model behavior through human-understandable concepts.

Representation Learning

MAML-en-LLM: Model Agnostic Meta-Training of LLMs for Improved In-Context Learning

no code implementations19 May 2024 Sanchit Sinha, Yuguang Yue, Victor Soto, Mayank Kulkarni, Jianhua Lu, Aidong Zhang

In this paper, we propose MAML-en-LLM, a novel method for meta-training LLMs, which can learn truly generalizable parameters that not only perform well on disjointed tasks but also adapts to unseen tasks.

In-Context Learning

A Self-explaining Neural Architecture for Generalizable Concept Learning

1 code implementation1 May 2024 Sanchit Sinha, Guangzhi Xiong, Aidong Zhang

With the wide proliferation of Deep Neural Networks in high-stake applications, there is a growing demand for explainability behind their decision-making process.

Concept Alignment Contrastive Learning +2

Enhance Diffusion to Improve Robust Generalization

1 code implementation5 Jun 2023 Jianhui Sun, Sanchit Sinha, Aidong Zhang

We approximate the dynamic of PGD-AT by a continuous-time Stochastic Differential Equation (SDE), and show that the diffusion term of this SDE determines the robust generalization.

Understanding and Enhancing Robustness of Concept-based Models

no code implementations29 Nov 2022 Sanchit Sinha, Mengdi Huai, Jianhui Sun, Aidong Zhang

Subsequently, we propose a potential general adversarial training-based defense mechanism to increase robustness of these systems to the proposed malicious attacks.

Decision Making Financial Analysis +1

Perturbing Inputs for Fragile Interpretations in Deep Natural Language Processing

1 code implementation EMNLP (BlackboxNLP) 2021 Sanchit Sinha, Hanjie Chen, Arshdeep Sekhon, Yangfeng Ji, Yanjun Qi

Via a small portion of word-level swaps, these adversarial perturbations aim to make the resulting text semantically and spatially similar to its seed input (therefore sharing similar interpretations).

Language Modeling Language Modelling

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