4 citations · 5 across the 12 of their papers we have counts for
17 papers
Evaluating Rubric Generation with Interventional Transfer
Erik Skalnes, Layne C. Price, Raviteja Anantha +1
Instance-specific rubrics are common in AI benchmarks where reliable evaluation requires specific expert knowledge. This approach is difficult to scale, prompting research into the…
Align-RAG: Alignment Is All You Need for TSFM In-Context Learning
Mohammad Asadi, Soheil Hor, Bardiya Akhbari +6
Retrieval-augmented forecasting promises to adapt frozen Time Series Foundation Models (TSFMs) to new domains without fine-tuning, but recent methods typically rely on learned fusi…
BoostLoRA: Growing Effective Rank by Boosting Adapters
Raviteja Anantha, Nick Levato, Layne C. Price
Parameter-efficient fine-tuning (PEFT) methods face a tradeoff between adapter size and expressivity: ultra-low-parameter adapters are confined to fixed low-rank subspaces, capping…
NanoFlux: Adversarial Dual-LLM Evaluation and Distillation For Multi-Domain Reasoning
Raviteja Anantha, Soheil Hor, Teodor Nicola Antoniu +1
We present NanoFlux, a novel adversarial framework for generating targeted training data to improve LLM reasoning, where adversarially-generated datasets containing fewer than 200…
CAMPHOR: Collaborative Agents for Multi-input Planning and High-Order Reasoning On Device
Yicheng Fu, Raviteja Anantha, Jianpeng Cheng
While server-side Large Language Models (LLMs) demonstrate proficiency in function calling and complex reasoning, deploying Small Language Models (SLMs) directly on devices brings…
UI-JEPA: Towards Active Perception of User Intent through Onscreen User Activity
Yicheng Fu, Raviteja Anantha, Prabal Vashisht +2
Generating user intent from a sequence of user interface (UI) actions is a core challenge in comprehensive UI understanding. Recent advancements in multimodal large language models…
Retrieval Augmented Correction of Named Entity Speech Recognition Errors
Ernest Pusateri, Anmol Walia, Anirudh Kashi +6
In recent years, end-to-end automatic speech recognition (ASR) systems have proven themselves remarkably accurate and performant, but these systems still have a significant error r…
Applying RLAIF for Code Generation with API-usage in Lightweight LLMs
Sujan Dutta, Sayantan Mahinder, Raviteja Anantha +1
Reinforcement Learning from AI Feedback (RLAIF) has demonstrated significant potential across various domains, including mitigating harm in LLM outputs, enhancing text summarizatio…
ProTIP: Progressive Tool Retrieval Improves Planning
Raviteja Anantha, Bortik Bandyopadhyay, Anirudh Kashi +3
Large language models (LLMs) are increasingly employed for complex multi-step planning tasks, where the tool retrieval (TR) step is crucial for achieving successful outcomes. Two p…
Context Tuning for Retrieval Augmented Generation
Raviteja Anantha, Tharun Bethi, Danil Vodianik +1
Large language models (LLMs) have the remarkable ability to solve new tasks with just a few examples, but they need access to the right tools. Retrieval Augmented Generation (RAG)…
DTW-SiameseNet: Dynamic Time Warped Siamese Network for Mispronunciation Detection and Correction
Raviteja Anantha, Kriti Bhasin, Daniela de la Parra Aguilar +3
Personal Digital Assistants (PDAs) - such as Siri, Alexa and Google Assistant, to name a few - play an increasingly important role to access information and complete tasks spanning…
Low-Resource Adaptation of Open-Domain Generative Chatbots
Greyson Gerhard-Young, Raviteja Anantha, Srinivas Chappidi +1
Recent work building open-domain chatbots has demonstrated that increasing model size improves performance. On the other hand, latency and connectivity considerations dictate the m…
A Wrong Answer or a Wrong Question? An Intricate Relationship between Question Reformulation and Answer Selection in Conversational Question Answering
Svitlana Vakulenko, Shayne Longpre, Zhucheng Tu +1
The dependency between an adequate question formulation and correct answer selection is a very intriguing but still underexplored area. In this paper, we show that question rewriti…
Open-Domain Question Answering Goes Conversational via Question Rewriting
Raviteja Anantha, Svitlana Vakulenko, Zhucheng Tu +3
We introduce a new dataset for Question Rewriting in Conversational Context (QReCC), which contains 14K conversations with 80K question-answer pairs. The task in QReCC is to find a…
Generalized Reinforcement Meta Learning for Few-Shot Optimization
Raviteja Anantha, Stephen Pulman, Srinivas Chappidi
We present a generic and flexible Reinforcement Learning (RL) based meta-learning framework for the problem of few-shot learning. During training, it learns the best optimization a…
Learning to Rank Intents in Voice Assistants
Raviteja Anantha, Srinivas Chappidi, William Dawoodi
Voice Assistants aim to fulfill user requests by choosing the best intent from multiple options generated by its Automated Speech Recognition and Natural Language Understanding sub…
Question Rewriting for Conversational Question Answering
Svitlana Vakulenko, Shayne Longpre, Zhucheng Tu +1
Conversational question answering (QA) requires the ability to correctly interpret a question in the context of previous conversation turns. We address the conversational QA task b…