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Found 13 papers, 9 papers with code
Case2Code: Learning Inductive Reasoning with Synthetic Data
In this paper, we hope to focus on evaluating and teaching LLMs to conduct inductive reasoning, that is, LLMs are supposed to infer underlying rules by observing examples or sequential transformations.
Scaling Laws for Fact Memorization of Large Language Models
We find that LLMs' fact knowledge capacity has a linear and negative exponential law relationship with model size and training epochs, respectively.
Cross-Modality Safety Alignment
As Artificial General Intelligence (AGI) becomes increasingly integrated into various facets of human life, ensuring the safety and ethical alignment of such systems is paramount.
Unified Active Retrieval for Retrieval Augmented Generation
Experiments on four representative types of user instructions show that UAR significantly outperforms existing work on the retrieval timing judgement and the performance of downstream tasks, which shows the effectiveness of UAR and its helpfulness to downstream tasks.
Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer Selection in Large Language Models
Recent advancements in Chain-of-Thought prompting have facilitated significant breakthroughs for Large Language Models (LLMs) in complex reasoning tasks.
Dictionary Learning Improves Patch-Free Circuit Discovery in Mechanistic Interpretability: A Case Study on Othello-GPT
Sparse dictionary learning has been a rapidly growing technique in mechanistic interpretability to attack superposition and extract more human-understandable features from model activations.
LLM can Achieve Self-Regulation via Hyperparameter Aware Generation
HAG extends the current paradigm in the text generation process, highlighting the feasibility of endowing the LLMs with self-regulate decoding strategies.
Can AI Assistants Know What They Don't Know?
To answer this question, we construct a model-specific "I don't know" (Idk) dataset for an assistant, which contains its known and unknown questions, based on existing open-domain question answering datasets.
Agent Alignment in Evolving Social Norms
Agents based on Large Language Models (LLMs) are increasingly permeating various domains of human production and life, highlighting the importance of aligning them with human values.
Evaluating Hallucinations in Chinese Large Language Models
We analyze the primary types of hallucinations in different types of models and their causes.
Improving Contrastive Learning of Sentence Embeddings from AI Feedback
Our method utilizes AI feedback from large pre-trained language models (LLMs) to construct sample pairs with fine-grained sample similarity scores to improve contrastive learning.
Mitigating Negative Style Transfer in Hybrid Dialogue System
As the functionality of dialogue systems evolves, hybrid dialogue systems that accomplish user-specific goals and participate in open-topic chitchat with users are attracting growing attention.
Is MultiWOZ a Solved Task? An Interactive TOD Evaluation Framework with User Simulator
Besides, we introduce a sentence-level and a session-level score to measure the sentence fluency and session coherence in the interactive evaluation.
