6 papers
Domain-Adapted Small Language Models with Hybrid Post-Processing: Achieving Cost-Efficient, Low-Latency Multi-Label Structured Prediction via LoRA Fine-Tuning on Scarce Data
Srinivasan Manoharan, Dilipkumar Nallusamy, Sachin Kumar +1
Deploying frontier large language models (LLMs) for domain-specific structured evaluation tasks incurs prohibitive latency, cost, and data-privacy overhead. We present a hybrid fra…
Leveraging Pretrained Language Models as Energy Functions for Glauber Dynamics Text Diffusion
Tarun Kathuria, Sachin Kumar
We present a discrete diffusion-based language model using Glauber dynamics from statistical physics. Our main insight is that instead of trying to train a discrete state space dif…
BASS: Benchmarking Audio LMs for Musical Structure and Semantic Reasoning
Min Jang, Orevaoghene Ahia, Nazif Tamer +3
Music understanding is a complex task that often requires reasoning over both structural and semantic elements of audio. We introduce BASS, designed to evaluate music understanding…
Hybrid Preferences: Learning to Route Instances for Human vs. AI Feedback
Lester James V. Miranda, Yizhong Wang, Yanai Elazar +6
Learning from human feedback has enabled the alignment of language models (LMs) with human preferences. However, collecting human preferences is expensive and time-consuming, with…
BLAB: Brutally Long Audio Bench
Orevaoghene Ahia, Martijn Bartelds, Kabir Ahuja +13
Developing large audio language models (LMs) capable of understanding diverse spoken interactions is essential for accommodating the multimodal nature of human communication and ca…
Steering off Course: Reliability Challenges in Steering Language Models
Patrick Queiroz Da Silva, Hari Sethuraman, Dheeraj Rajagopal +2
Steering methods for language models (LMs) have gained traction as lightweight alternatives to fine-tuning, enabling targeted modifications to model activations. However, prior stu…