In human conversation, both interlocutors play an active role in maintaining mutual understanding. When addressees are uncertain about what speakers mean, for e...
The increased use of Large Language Models (LLMs) in sensitive domains leads to growing interest in how their confidence scores correspond to fairness and bias....
Large language models (LLMs) are increasingly used as conversational partners for learning, yet the interactional dynamics supporting users' learning and engage...
Large language models (LLMs) are increasingly evaluated on their ability to perform multi-hop reasoning, i.e., to combine multiple pieces of information into a ...
LLM agents operating over massive, dynamic tool libraries rely on effective retrieval, yet standard single-shot dense retrievers struggle with complex requests....
While Chain-of-Thought (CoT) prompting advances LLM reasoning, challenges persist in consistency, accuracy, and self-correction, especially for complex or ethic...
While Vision-Language Models (VLMs) have significantly advanced Computer-Using Agents (CUAs), current frameworks struggle with robustness in long-horizon workfl...
Large Language Models (LLMs) can produce surprisingly sophisticated estimates of their own uncertainty. However, it remains unclear to what extent this expresse...
Understanding narratives requires identifying which events are most salient for a story's progression. We present a contrastive learning framework for modeling ...
Numerical reasoning is an important task in the analysis of financial documents. It helps in understanding and performing numerical predictions with logical con...
How I used n8n to build AI study partners for learning Mandarin: vocabulary, listening, and pronunciation correction. The post How AI Can Become Your Personal L...
Looking at the performance of different pipelines The post When Does Adding Fancy RAG Features Work? appeared first on Towards Data Science....
