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Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering
This research paper argues that current methods for Uncertainty Quantification (UQ) in large language models are fundamentally flawed because they fu…
2 months ago
Position: Agents Should Invoke External Tools ONLY When Epistemically Necessary
This position paper discusess Theory of Agent (ToA), a framework that redefines large language model agents as decision-makers who must choose betwee…
2 months ago
From conversations to mechanisms: aligning advertiser Incentives in ai-powered product recommendations
This research paper explores the development of efficient recommendation systems, such as AI shopping assistants, that manage multi-round interaction…
2 months ago
Is one layer enough? Training a single transformer layer can match full-parameter RL training
This paper explores a surprising structural property of large language models: most reinforcement learning (RL) gains are concentrated in a very smal…
2 months ago
RL Excursions during Pre-Training: Re-examining Policy Optimization for LLM training
This research investigates the effectiveness of integrating reinforcement learning (RL) earlier in the large language model training pipeline rather …
2 months ago
Language Generation with Feedback: Queries and Mistakes
This paper introduces a theoretical framework for language generation in the limit, exploring how machines can learn to produce valid, unseen strings…
2 months ago
Quantifying Theoretical AI Alignment Guarantees: Receiver-Utility Bounds in Bayesian Persuasion
This research paper explores theoretical AI alignment through the lens of Bayesian persuasion, specifically examining how a misaligned AI agent might…
2 months, 1 week ago
SPIRAL: Learning to search and aggregate
The Spiral framework addresses a limitation in current language model training where models are optimized for single-trace reasoning but fail to coor…
2 months, 1 week ago
Qwen-AgentWorld: Language World Models for General Agents
We discuss Qwen-AgentWorld, a pioneering suite of language world models designed to simulate complex digital environments for artificial intelligence…
2 months, 1 week ago
When Does Trajectory-Level Supervision Permit Efficient Offline Reinforcement Learning?
This paper discusses a statistical framework for offline reinforcement learning using trajectory-level supervision, where only final outcomes or pref…
2 months, 1 week ago