1 citations · 1 across the 6 of their papers we have counts for
7 papers
INTACT: Inducing Latent Reasoning on a Frozen Backbone
Kutay Tire, Atula Tejaswi, Haris Vikalo +1
Latent reasoning replaces natural-language chains of thought with compact continuous "soft-token" representations, reducing the number of intermediate tokens that must be decoded a…
Reward-Gated On-Policy Distillation
Mohammad Sadegh Akhondzadeh, Vijay Lingam, Atula Tejaswi +3
On-policy distillation is a powerful way to transfer reasoning ability from a strong teacher to a smaller student: the student samples trajectories from its own policy, and the tea…
OpenThoughts-Agent: Data Recipes for Agentic Models
Negin Raoof, Richard Zhuang, Marianna Nezhurina +47
Agentic language models dramatically expand the applications of AI yet little is publicly known about how to curate training data for broadly capable agents. Existing open efforts…
Entropy Aware Reward Guidance for Diffusion Language Model Alignment
Atula Tejaswi, Litu Rout, Constantine Caramanis +2
Reward guidance, also known as posterior sampling, is a popular method for test-time adaptation and post-training in continuous diffusion models. In this paper, we study reward gui…
RARe: Retrieval Augmented Retrieval with In-Context Examples
Atula Tejaswi, Yoonsang Lee, Sujay Sanghavi +1
While in-context learning is well-studied with decoder-only language models (LLMs), its utility for encoder-only models remains underexplored. We study in-context learning for enco…
Exploring Design Choices for Building Language-Specific LLMs
Atula Tejaswi, Nilesh Gupta, Eunsol Choi
Despite rapid progress in large language models (LLMs), their performance on a vast majority of languages remains unsatisfactory. In this paper, we study building language-specific…
SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors
Vijay Lingam, Atula Tejaswi, Aditya Vavre +7
Popular parameter-efficient fine-tuning (PEFT) methods, such as LoRA and its variants, freeze pre-trained model weights \(W\) and inject learnable matrices \(ΔW\). These \(ΔW\) mat…