7 papers
The Illusion of Generalization in Tabular Language Models
Aditya Gorla, Ratish Puduppully
Tabular Language Models (TLMs) have been claimed to achieve strong generalization for tabular prediction. We conduct a systematic re-evaluation of Tabula-8B as a representative TLM…
IndicIFEval: A Benchmark for Verifiable Instruction-Following Evaluation in 14 Indic Languages
Thanmay Jayakumar, Mohammed Safi Ur Rahman Khan, Raj Dabre +2
Instruction-following benchmarks remain predominantly English-centric, leaving a critical evaluation gap for the hundreds of millions of Indic language speakers. We introduce Indic…
The Reasoning Lingua Franca: A Double-Edged Sword for Multilingual AI
Alan Saji, Raj Dabre, Anoop Kunchukuttan +1
Large Reasoning Models (LRMs) achieve strong performance on mathematical, scientific, and other question-answering tasks, but their multilingual reasoning abilities remain underexp…
RiddleBench: A New Generative Reasoning Benchmark for LLMs
Deepon Halder, Alan Saji, Thanmay Jayakumar +3
Large Language Models have demonstrated strong performance on many established reasoning benchmarks. However, these benchmarks primarily evaluate structured skills like quantitativ…
Chimera: State Space Models Beyond Sequences
Aakash Lahoti, Tanya Marwah, Ratish Puduppully +1
Transformer-based deep learning methods have become the standard approach for modeling diverse data such as sequences, images, and graphs. These methods rely on self-attention, whi…
Improving Genomic Models via Task-Specific Self-Pretraining
Sohan Mupparapu, Parameswari Krishnamurthy, Ratish Puduppully
Pretraining DNA language models (DNALMs) on the full human genome is resource-intensive, yet often considered necessary for strong downstream performance. Inspired by recent findin…