Papers by Anushka Sivakumar
SteerVLM: Robust Model Control through Lightweight Activation Steering for Vision Language Models (2025.findings-emnlp)
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| Challenge: | SteerVLM is a lightweight steering module designed to guide Vision-Language Models (VLMs) towards outputs that better adhere to desired instructions. |
| Approach: | They propose a lightweight steering module that learns from latent embeddings of paired prompts encoding target and converse behaviors to dynamically adjust activations connecting the language modality with image context. |
| Outcome: | The proposed steering module outperforms existing intervention techniques on steering and hallucination mitigation benchmarks for VLMs. |
Maximal Matching Matters: Preventing Representation Collapse for Robust Cross-Modal Retrieval (2025.acl-long)
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| Challenge: | Existing approaches to cross-modal image-text retrieval struggle with nuanced cross-modal relationships. |
| Approach: | They propose a set-based approach that represents each sample with multiple embeddings to capture nuanced and diverse relationships. |
| Outcome: | The proposed method achieves state-of-the-art performance on MS-COCO and Flickr30k without external data. |
Flexible-length Text Infilling for Discrete Diffusion Models (2025.emnlp-main)
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| Challenge: | Existing discrete diffusion models lack flexibility for text infilling without ground-truth positional data. |
| Approach: | They propose a discrete diffusion model that jointly denoises token values and token positions using a novel sample-level Optimal Transport coupling. |
| Outcome: | The proposed method outperforms existing methods on infilling benchmarks such as One-Billion-Word and Yelp. |