AI Papers of the Week
Every paper worth reading in AI, hand-picked one week at a time.
Survey on Factuality in LLMs
A survey covering evaluation and enhancement techniques for LLM factuality.
LLMs for Healthcare Survey
A comprehensive overview of LLMs applied to the healthcare domain.
InstructRetro
NVIDIA introduces Retro 48B, the largest LLM pretrained with retrieval at the time.
FireAct (Language Agent Fine-tuning)
Explores fine-tuning LLMs specifically for language-agent use, demonstrating consistent gains over prompting alone.
LLMs Represent Space and Time
MIT researchers find that LLMs internally encode linear representations of space and time across multiple scales.
Retrieval Meets Long-Context LLMs
NVIDIA's study comparing RAG and long-context LLMs, with the punchline that the two are complementary rather than substitutes.
RA-DIT (Retrieval-Augmented Dual Instruction Tuning)
Meta's RA-DIT is a lightweight recipe that retrofits LLMs with retrieval capabilities through dual fine-tuning.
Analogical Prompting
Google's Analogical Prompting guides LLM reasoning by having the model self-generate relevant exemplars on the fly.
Effective Long-Context Scaling (Meta)
Meta proposes a 70B long-context LLM that surpasses GPT-3.5-turbo-16k on long-context benchmarks.
Graph Neural Prompting (GNP)
A plug-and-play method that injects knowledge-graph information into frozen pretrained LLMs.
Boolformer
The first Transformer trained to perform end-to-end symbolic regression of Boolean functions.
LLaVA-RLHF
Adapts factually augmented RLHF to aligning large multimodal models, reducing hallucination without falling into reward-hacking pitfalls.
LLM Alignment Survey
A comprehensive survey of LLM alignment research spanning theoretical foundations to adversarial pressure.
Qwen
Alibaba releases the Qwen family of open LLMs with strong tool-use and planning capabilities for language agents.
Logical Chain-of-Thought (LogiCoT)
A neurosymbolic framework that verifies and revises zero-shot CoT reasoning using symbolic-logic principles.
Contrastive Decoding for Reasoning
Shows that contrastive decoding, a simple inference-time technique, substantially improves reasoning in large LLMs.
Struc-Bench (LLMs for Structured Data)
Studies how LLMs handle complex structured-data generation and proposes a structure-aware fine-tuning method.
LMSYS-Chat-1M
LMSYS releases a large-scale dataset of 1 million real-world LLM conversations collected from the Vicuna demo and Chatbot Arena.
OWL (LLMs for IT Operations)
Proposes OWL, an LLM specialized for IT operations through self-instruct fine-tuning on IT-specific tasks.
Rewindable Auto-regressive INference (RAIN)
Shows that unaligned LLMs can produce aligned responses at inference time via self-evaluation and rewinding.
Hallucination Survey (Early)
Classifies hallucination phenomena in LLMs and catalogs evaluation criteria and mitigation strategies.
Radiology-Llama 2
A Llama 2-based LLM specialized for radiology report generation.
MAmmoTH
An open-source LLM family specialized for general mathematical problem solving.
Overview of AI Deception
A survey cataloguing empirical examples of AI systems exhibiting deceptive behavior.