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Found 6 papers, 2 papers with code
WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning
While reinforcement learning (RL) has demonstrated remarkable success in enhancing large language models (LLMs), it has primarily focused on single-turn tasks such as solving math problems.
Improving Tool Retrieval by Leveraging Large Language Models for Query Generation
By conducting extensive experiments on a dataset covering complex and multi-tool scenarios, we show that leveraging LLMs for query generation improves the retrieval for in-domain (seen tools) and out-of-domain (unseen tools) settings.
Open World Classification with Adaptive Negative Samples
Open world classification is a task in natural language processing with key practical relevance and impact.
Ranking-Enhanced Unsupervised Sentence Representation Learning
In this work, we show that the semantic meaning of a sentence is also determined by nearest-neighbor sentences that are similar to the input sentence.
An End-to-end Approach for Handling Unknown Slot Values in Dialogue State Tracking
We highlight a practical yet rarely discussed problem in dialogue state tracking (DST), namely handling unknown slot values.
A Model for Temporal Dependencies in Event Streams
We introduce the Piecewise-Constant Conditional Intensity Model, a model for learning temporal dependencies in event streams.
