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The BatchNorm Illusion: Diagnosing Normalization Artifacts in Machine Unlearning Evaluation
Aaryaman Kalani, Murari Mandal, Dhruv Kumar +2
Approximate machine unlearning aims to remove the influence of specific training data from a trained model without retraining from scratch. We identify a previously undocumented co…
Where Computation Lives Inside TabPFN: Causal Localisation of Attention Head Function
Atharva Gupta, Dhruv Kumar, Murari Mandal +1
We present the first causal mechanistic analysis of a tabular foundation model, investigating how TabPFN 2.5's feature wise attention heads distribute computation across layers. Us…
Mix, Don't Pick: Why Synthetic Corpus Composition Matters for Time Series Foundation Model Pretraining
Aaryan Nagpal, Debdeep Sanyal, Murari Mandal +2
Choosing the wrong synthetic generator for time-series foundation model pretraining is costly: under identical training budgets, the best and worst generators produce up to a $2\ti…
REGEN: Reference-Guided Synthetic Multivariate Time Series Generation for Forecasting
Moulik Gupta, Dhruv Kumar, Murari Mandal +1
Training robust multivariate time series forecasting models requires large, diverse corpora, yet many real-world domains provide only a handful of observed sequences. Existing gene…
Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models
Ashutosh Ranjan, Vivek Srivastava, Shirish Karande +1
Deployed text-to-image diffusion models increasingly require post-hoc concept unlearning for copyright claims, artist opt-outs, safety updates, and protected-content mitigation wit…
time2time: Causal Intervention in Hidden States to Simulate Rare Events in Time Series Foundation Models
Debdeep Sanyal, Aaryan Nagpal, Dhruv Kumar +2
While transformer-based foundation models excel at forecasting routine patterns, two questions remain: do they internalize semantic concepts such as market regimes, or merely fit c…
Unlearning or Concealment? A Critical Analysis and Evaluation Metrics for Unlearning in Diffusion Models
Aakash Sen Sharma, Niladri Sarkar, Vikram Chundawat +2
Recent research has seen significant interest in methods for concept removal and targeted forgetting in text-to-image diffusion models. In this paper, we conduct a comprehensive wh…
A Unified Framework for Continual Learning and Unlearning
Romit Chatterjee, Vikram Chundawat, Ayush Tarun +2
Continual learning and machine unlearning are crucial challenges in machine learning, typically addressed separately. Continual learning focuses on adapting to new knowledge while…