Zobrazeno 1 - 10
of 18 958
pro vyhledávání: '"A, Ramamurthy"'
Autor:
Butt, Shahzad Ahmad, Reynolds, Benjamin, Ramamurthy, Veeraraghavan, Xiao, Xiao, Chu, Pohrong, Sharifian, Setareh, Gribok, Sergey, Pasca, Bogdan
Zero-Knowledge Proofs (ZKPs) have emerged as an important cryptographic technique allowing one party (prover) to prove the correctness of a statement to some other party (verifier) and nothing else. ZKPs give rise to user's privacy in many applicatio
Externí odkaz:
http://arxiv.org/abs/2412.12481
Autor:
Wei, Dennis, Padhi, Inkit, Ghosh, Soumya, Dhurandhar, Amit, Ramamurthy, Karthikeyan Natesan, Chang, Maria
Training data attribution (TDA) is the task of attributing model behavior to elements in the training data. This paper draws attention to the common setting where one has access only to the final trained model, and not the training algorithm or inter
Externí odkaz:
http://arxiv.org/abs/2412.03906
Hyperkinetic movement disorders (HMDs) in children, including dystonia (abnormal twisting) and chorea (irregular, random movements), pose significant diagnostic challenges due to overlapping clinical features. The prevalence of dystonia ranges from 2
Externí odkaz:
http://arxiv.org/abs/2411.15200
Autor:
Miehling, Erik, Desmond, Michael, Ramamurthy, Karthikeyan Natesan, Daly, Elizabeth M., Dognin, Pierre, Rios, Jesus, Bouneffouf, Djallel, Liu, Miao
Building pluralistic AI requires designing models that are able to be shaped to represent a wide range of value systems and cultures. Achieving this requires first being able to evaluate the degree to which a given model is capable of reflecting vari
Externí odkaz:
http://arxiv.org/abs/2411.12405
We investigate the use of labelled graphs as a Morita equivalence invariant for inverse semigroups. We construct a labelled graph from a combinatorial inverse semigroup $S$ with $0$ admitting a special set of idempotent $\mathcal{D}$-class representa
Externí odkaz:
http://arxiv.org/abs/2411.09015
Autor:
Ramamurthy, Rajkumar, Rajeev, Meghana Arakkal, Molenschot, Oliver, Zou, James, Rajani, Nazneen
Large language models (LLMs) often fail to synthesize information from their context to generate an accurate response. This renders them unreliable in knowledge intensive settings where reliability of the output is key. A critical component for relia
Externí odkaz:
http://arxiv.org/abs/2411.03300
Mechanistic interpretability aims to provide human-understandable insights into the inner workings of neural network models by examining their internals. Existing approaches typically require significant manual effort and prior knowledge, with strate
Externí odkaz:
http://arxiv.org/abs/2410.16484
Autor:
Trivedi, Prapti, Gulati, Aditya, Molenschot, Oliver, Rajeev, Meghana Arakkal, Ramamurthy, Rajkumar, Stevens, Keith, Chaudhery, Tanveesh Singh, Jambholkar, Jahnavi, Zou, James, Rajani, Nazneen
LLM-as-a-judge models have been used for evaluating both human and AI generated content, specifically by providing scores and rationales. Rationales, in addition to increasing transparency, help models learn to calibrate its judgments. Enhancing a mo
Externí odkaz:
http://arxiv.org/abs/2410.05495
Autor:
Lee, Bruce W., Padhi, Inkit, Ramamurthy, Karthikeyan Natesan, Miehling, Erik, Dognin, Pierre, Nagireddy, Manish, Dhurandhar, Amit
LLMs have shown remarkable capabilities, but precisely controlling their response behavior remains challenging. Existing activation steering methods alter LLM behavior indiscriminately, limiting their practical applicability in settings where selecti
Externí odkaz:
http://arxiv.org/abs/2409.05907
Autor:
Padhi, Inkit, Ramamurthy, Karthikeyan Natesan, Sattigeri, Prasanna, Nagireddy, Manish, Dognin, Pierre, Varshney, Kush R.
Aligning large language models (LLMs) to value systems has emerged as a significant area of research within the fields of AI and NLP. Currently, this alignment process relies on the availability of high-quality supervised and preference data, which c
Externí odkaz:
http://arxiv.org/abs/2408.10392