activity
20202026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 711 across the 35 of their papers we have counts for

collaborators
Showing 2025Show all

7 papers · 1 filter

cs.CL2025

Adversarial Lens: Exploiting Attention Layers to Generate Adversarial Examples for Evaluation

Kaustubh Dhole

Recent advances in mechanistic interpretability suggest that intermediate attention layers encode token-level hypotheses that are iteratively refined toward the final output. In th…

cs.CL2025

Toward Honest Language Models for Deductive Reasoning

Jiarui Liu, Kaustubh Dhole, Yingheng Wang +7

Deductive reasoning is the process of deriving conclusions strictly from the given premises, without relying on external knowledge. We define honesty in this setting as a model's a…

cs.CL2025

Evaluating Hybrid Retrieval Augmented Generation using Dynamic Test Sets: LiveRAG Challenge

Chase Fensore, Kaustubh Dhole, Joyce C Ho +1

We present our submission to the LiveRAG Challenge 2025, which evaluates retrieval-augmented generation (RAG) systems on dynamic test sets using the FineWeb-10BT corpus. Our final…

cs.IR2025

InsertRank: LLMs can reason over BM25 scores to Improve Listwise Reranking

Rahul Seetharaman, Kaustubh D. Dhole, Aman Bansal

Large Language Models (LLMs) have demonstrated significant strides across various information retrieval tasks, particularly as rerankers, owing to their strong generalization and k…

cs.IR2025

Generative Product Recommendations for Implicit Superlative Queries

Kaustubh D. Dhole, Nikhita Vedula, Saar Kuzi +3

In Recommender Systems, users often seek the best products through indirect, vague, or under-specified queries, such as "best shoes for trail running". Such queries, also referred…

cs.CL2025

A Multi-Encoder Frozen-Decoder Approach for Fine-Tuning Large Language Models

Kaustubh D. Dhole

Among parameter-efficient fine-tuning methods, freezing has emerged as a popular strategy for speeding up training, reducing catastrophic forgetting, and improving downstream perfo…

cs.CL2025★ 1 cited

To Retrieve or Not to Retrieve? Uncertainty Detection for Dynamic Retrieval Augmented Generation

Kaustubh D. Dhole

Retrieval-Augmented Generation equips large language models with the capability to retrieve external knowledge, thereby mitigating hallucinations by incorporating information beyon…