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Tom Goldstein

Papers
48

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48papers

Authored papers

48

Image Generation with a Sphere Encoder

arXiv 2026

2026

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

arXiv 2025

2025

The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text

arXiv 2025

2025

LoRI: Reducing Cross-Task Interference in Multi-Task Low-Rank Adaptation

arXiv 2025

2025

Zero-Shot Vision Encoder Grafting via LLM Surrogates

ICCV 2025

2025

Teaching Pretrained Language Models to Think Deeper with Retrofitted Recurrence

arXiv 2025

2025

Gemstones: A Model Suite for Multi-Faceted Scaling Laws

arXiv 2025

2025

Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning

arXiv 2025

2025

ARGUS: Hallucination and Omission Evaluation in Video-LLMs

ICCV 2025

2025

MORSE-500: A Programmatically Controllable Video Benchmark to Stress-Test Multimodal Reasoning

arXiv 2025

2025

Has My System Prompt Been Used? Large Language Model Prompt Membership Inference

arXiv 2025

2025

DynaGuard: A Dynamic Guardrail Model With User-Defined Policies

arXiv 2025

2025

When Can You Get Away with Low Memory Adam?

arXiv 2025

2025

Exploiting Sparsity for Long Context Inference: Million Token Contexts on Commodity GPUs

arXiv 2025

2025

LiveBench: A Challenging, Contamination-Limited LLM Benchmark

arXiv 2024

2024

Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text

arXiv 2024

2024

Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models

arXiv 2024

2024

Coercing LLMs to do and reveal (almost) anything

arXiv 2024

2024

What do we learn from inverting CLIP models?

arXiv 2024

2024

The CLRS-Text Algorithmic Reasoning Language Benchmark

arXiv 2024

2024

Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs

arXiv 2024

2024

WAVES: Benchmarking the Robustness of Image Watermarks

arXiv 2024

2024

Transformers Can Do Arithmetic with the Right Embeddings

arXiv 2024

2024

Measuring Style Similarity in Diffusion Models

arXiv 2024

2024

Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion

arXiv 2024

2024

Benchmarking ChatGPT on Algorithmic Reasoning

arXiv 2024

2024

NEFTune: Noisy Embeddings Improve Instruction Finetuning

arXiv 2023

2023

On the Reliability of Watermarks for Large Language Models

arXiv 2023

2023

Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks

NeurIPS 2023 11

2023

Understanding and Mitigating Copying in Diffusion Models

understanding-and-mitigating-copying-in

2023

Bring Your Own Data! Self-Supervised Evaluation for Large Language Models

arXiv 2023

2023

On the Exploitability of Instruction Tuning

on-the-exploitability-of-instruction-tuning

2023

Universal Guidance for Diffusion Models

arXiv 2023

2023

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

hard-prompts-made-easy-gradient-based

2023

Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust

arXiv 2023

2023

InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models

arXiv 2023

2023

Object Recognition as Next Token Prediction

CVPR 2024 1

2023

Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise

cold-diffusion-inverting-arbitrary-image

2022

Cramming: Training a Language Model on a Single GPU in One Day

arXiv 2022

2022

Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries

arXiv 2022

2022

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models

arXiv 2022

2022

What do Vision Transformers Learn? A Visual Exploration

arXiv 2022

2022

Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations

plug-in-inversion-model-agnostic-inversion

2022

Stochastic Training is Not Necessary for Generalization

stochastic-training-is-not-necessary-for-1

2021

Datasets for Studying Generalization from Easy to Hard Examples

arXiv 2021

2021

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

saint-improved-neural-networks-for-tabular-1

2021

Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features

arXiv 2021

2021

Visualizing the Loss Landscape of Neural Nets

visualizing-the-loss-landscape-of-neural-nets-1

2017

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from 48 papers