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Found 11 papers, 5 papers with code
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis
To address these challenges, we propose OS-Genesis, a novel GUI data synthesis pipeline that reverses the conventional trajectory collection process.
OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
Existing efforts in building GUI agents heavily rely on the availability of robust commercial Vision-Language Models (VLMs) such as GPT-4o and GeminiProVision.
Ranked #3 on
Natural Language Visual Grounding
on ScreenSpot
MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture of Shards
The rapid scaling of large language models necessitates more lightweight finetuning methods to reduce the explosive GPU memory overhead when numerous customized models are served simultaneously.
How Well Do LLMs Handle Cantonese? Benchmarking Cantonese Capabilities of Large Language Models
The rapid evolution of large language models (LLMs) has transformed the competitive landscape in natural language processing (NLP), particularly for English and other data-rich languages.
Data Augmentation of Multi-turn Psychological Dialogue via Knowledge-driven Progressive Thought Prompting
The thought generated by the progressive thought generator serves as a prompt to prevent the generated dialogue from having significant semantic deviations, while the psychology knowledge generator produces psychological knowledge to serve as the dialogue history for the LLM, guiding the dialogue generator to create multi-turn psychological dialogue.
LoRA Meets Dropout under a Unified Framework
Hence, a possible contradiction arises from negligible trainable parameters of LoRA and the effectiveness of previous dropout methods, which has been largely overlooked.
PRoLoRA: Partial Rotation Empowers More Parameter-Efficient LoRA
Hopefully, the conspicuously higher parameter efficiency can establish PRoLoRA as a resource-friendly alternative to LoRA.
Diffusion of Thoughts: Chain-of-Thought Reasoning in Diffusion Language Models
Recently, diffusion models have garnered significant interest in the field of text processing due to their many potential advantages compared to conventional autoregressive models.
Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning
Although existing works formulate this problem into a centralized learning with decentralized execution framework, which avoids the non-stationary problem in training, their decentralized execution paradigm limits the agents' capability to coordinate.
Multi-agent Reinforcement Learning
reinforcement-learning
+2
Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence
Knowledge base is one of the main forms to represent information in a structured way.
Sampled in Pairs and Driven by Text: A New Graph Embedding Framework
TGE-PS uses Pairs Sampling (PS) to improve the sampling strategy of RW, being able to reduce ~99% training samples while preserving competitive performance.
