5 papers · 1 filter
Characterizing Mamba's Selective Memory using Auto-Encoders
Tamanna Hossain, Robert L. Logan, Ganesh Jagadeesan +3
State space models (SSMs) are a promising alternative to transformers for language modeling because they use fixed memory during inference. However, this fixed memory usage require…
Leveraging In-Context Learning for Language Model Agents
Shivanshu Gupta, Sameer Singh, Ashish Sabharwal +2
In-context learning (ICL) with dynamically selected demonstrations combines the flexibility of prompting large language models (LLMs) with the ability to leverage training data to…
Nudging: Inference-time Alignment of LLMs via Guided Decoding
Yu Fei, Yasaman Razeghi, Sameer Singh
Large language models (LLMs) require alignment to effectively and safely follow user instructions. This process necessitates training an aligned version for every base model, resul…
Semantic Probabilistic Control of Language Models
Kareem Ahmed, Catarina G Belem, Padhraic Smyth +1
Semantic control entails steering LM generations towards satisfying subtle non-lexical constraints, e.g., toxicity, sentiment, or politeness, attributes that can be captured by a s…
TurtleBench: A Visual Programming Benchmark in Turtle Geometry
Sina Rismanchian, Yasaman Razeghi, Sameer Singh +1
Humans have the ability to reason about geometric patterns in images and scenes from a young age. However, developing large multimodal models (LMMs) capable of similar reasoning re…