Robots that ask for help: Uncertainty alignment for large language model planners
Large language models (LLMs) exhibit a wide range of promising capabilities--from step-by-
step planning to commonsense reasoning--that may provide utility for robots, but remain …
step planning to commonsense reasoning--that may provide utility for robots, but remain …
Trustworthy LLMs: A survey and guideline for evaluating large language models' alignment
Ensuring alignment, which refers to making models behave in accordance with human
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …
Uncertainty in natural language generation: From theory to applications
Recent advances of powerful Language Models have allowed Natural Language
Generation (NLG) to emerge as an important technology that can not only perform traditional …
Generation (NLG) to emerge as an important technology that can not only perform traditional …
Conformal prediction for natural language processing: A survey
The rapid proliferation of large language models and natural language processing (NLP)
applications creates a crucial need for uncertainty quantification to mitigate risks such as …
applications creates a crucial need for uncertainty quantification to mitigate risks such as …
Benchmarking llms via uncertainty quantification
The proliferation of open-source Large Language Models (LLMs) from various institutions
has highlighted the urgent need for comprehensive evaluation methods. However, current …
has highlighted the urgent need for comprehensive evaluation methods. However, current …
Forking uncertainties: Reliable prediction and model predictive control with sequence models via conformal risk control
In many real-world problems, predictions are leveraged to monitor and control cyber-
physical systems, demanding guarantees on the satisfaction of reliability and safety …
physical systems, demanding guarantees on the satisfaction of reliability and safety …
Knowing when to stop: Delay-adaptive spiking neural network classifiers with reliability guarantees
Spiking neural networks (SNNs) process time-series data via internal event-driven neural
dynamics. The energy consumption of an SNN depends on the number of spikes exchanged …
dynamics. The energy consumption of an SNN depends on the number of spikes exchanged …
Conformal autoregressive generation: Beam search with coverage guarantees
We introduce two new extensions to the beam search algorithm based on conformal
predictions (CP) to produce sets of sequences with theoretical coverage guarantees. The …
predictions (CP) to produce sets of sequences with theoretical coverage guarantees. The …
Prompt risk control: A rigorous framework for responsible deployment of large language models
The recent explosion in the capabilities of large language models has led to a wave of
interest in how best to prompt a model to perform a given task. While it may be tempting to …
interest in how best to prompt a model to perform a given task. While it may be tempting to …
C-rag: Certified generation risks for retrieval-augmented language models
Despite the impressive capabilities of large language models (LLMs) across diverse
applications, they still suffer from trustworthiness issues, such as hallucinations and …
applications, they still suffer from trustworthiness issues, such as hallucinations and …