3 citations · 5 across the 17 of their papers we have counts for
8 papers · 1 filter
COILD: An Indic-Centric Parallel Corpus and Benchmark for Machine Translation Across Indian Languages
Kshetrimayum Boynao Singh, Nitin Kumar Mishra, Palash Pratim Dutta +22
Machine translation (MT) for Indian languages remains constrained by the limited availability of high-quality, Indic-centric parallel corpora and evaluation benchmarks. Existing mu…
AUDITPLAN: Commit, Then Answer for Auditable Safety Alignment
Sai Sri Pushpa Jampani, Kshitij Mishra, Asif Ekbal
Safety tuning pipelines judge only the final answer, which makes it difficult to distinguish robust refusal from two undesirable shortcuts: blanket refusal on benign requests and p…
Source-Free MT Evaluation Is Not MT Evaluation
Baban Gain, Ramakrishna Appicharla, Asif Ekbal
Reference-based metrics remain the standard choice in machine translation evaluation, partly because quality estimation methods often correlate less well with human judgments. As a…
GPUAlert: A Zero-Instrumentation Process-Boundary Monitor for Diagnosing GPU Training-Job Failures
Parv Agarwal, Asif Ekbal
GPU training jobs fail often, roughly two in five on large production clusters, yet the operator typically learns of a failure only by reconnecting hours later. Experiment trackers…
Which Tokens Need Context? A Reference-Based Analysis of Translation Responsibility Using Fertility and Entropy
Ramakrishna Appicharla, Baban Gain, Santanu Pal +1
When humans translate, not every word depends equally on the surrounding context. Some tokens, particularly function words like pronouns and auxiliaries, rely heavily on preceding…
When Can We Trust the Sparse Lens? A Certification Framework for SAE Faithfulness
Dibyanayan Bandyopadhyay, Asif Ekbal
Sparse autoencoders (SAEs) are increasingly used to study internal representations in language models (LMs), but it remains unclear when an SAE-based representation reliably preser…
One Model to Translate Them All? A Journey to Mount Doom for Multilingual Model Merging
Baban Gain, Trilok Nath Singh, Asif Ekbal
Weight-space model merging combines independently fine-tuned checkpoints without access to the original training data. While merging has shown promise in multitask settings, its be…
Sparse Semantic Dimension as a Generalization Certificate for LLMs
Dibyanayan Bandyopadhyay, Asif Ekbal
Standard statistical learning theory predicts that Large Language Models (LLMs) should overfit because their parameter counts vastly exceed the number of training tokens. Yet, in p…