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DAIR.AI Profile picture
@dair_ai
Jan 19 • 11 tweets • 4 min read • Read on X
Here are the top AI Papers of the Week (Jan 13-19):

- VideoRAG
- MiniMax-01
- Enhancing RAG
- Self-Adaptive LLMs
- Foundations of LLMs
- Learning to Memorize at Test Time

Read on for more:
1). Self-Adaptive LLMs - introduces Transformer^2, a novel self-adaptation framework that adapts LLMs for unseen tasks in real-time by selectively adjusting singular components of their weight matrices...

2). MiniMax-01 - introduces a new series of models that integrate Mixture-of-Experts; introduces a model with 32 experts and 456B parameters, and 45.9B are activated for each token...

3). VideoRAG - a framework that enhances RAG by leveraging video content as an external knowledge source...

4). Learning to Memorize at Test Time - introduces a neural long-term memory module to memorize historical context and help attention to attend to the current context while utilizing long past information.

5). Foundations of LLMs - new survey on the foundations of LLMs covering areas such as pre-training, prompting, and alignment methods.

6). OmniThink - a new framework that emulates a human-like process of iterative expansion and reflection...

7). Enhancing RAG - systematically explores the factors and methods that improve RAG systems such as retrieval strategies, query expansion, contrastive in-context learning, prompt design, and chunking.

8). AutoCBT - proposes a multi-agent framework, AutoCBT, for Cognitive Behavioral Therapy; the work proposes a general multi-agent framework that generates high-quality responses for single-turn psychological consultation scenarios...

9). Imagine while Reasoning in Space - introduces MVoT (Multimodal Visualization-of-Thought), a new reasoning framework that enables AI models to "think" in both text and image.

10). ChemAgent - presents a new framework designed to improve the performance of LLMs on chemical reasoning through a dynamic, self-updating library...

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More from @dair_ai

DAIR.AI Profile picture
Dec 29, 2024
Here are the top ML Papers of the Week (Dec 16-22):

- DRT-o1
- LearnLM
- DeepSeek-V3
- Large Concept Models
- Explore Theory-of-Mind
- Reinforcement Learning Overview

Read on for more:
1). DeepSeek-V3 - a 671B-parameter MoE language model that activates 37B parameters per token, utilizing MLA and DeepSeekMoE architectures for efficient operation

2). Large Concept Models - presents an approach that operates on sentence-level semantic representations called concepts, moving beyond token-level processing typical in current LLMs.

Read 11 tweets
DAIR.AI Profile picture
Dec 22, 2024
Here are the top ML Papers of the Week (Dec 16-22):

- Genesis
- AutoFeedback
- TheAgentCompany
- Alignment Faking in LLMs
- Qwen-2.5 Technical Report
- Precise Length Control in LLMs

Read on for more:
1). Genesis - a new universal physics simulation platform that combines a high-performance physics engine with generative AI capabilities...

2). Alignment Faking in LLMs - demonstrates that the Claude model can engage in "alignment faking"; it can strategically comply with harmful requests to avoid retraining while preserving its original safety preferences; this raises concerns about the reliability of AI safety training methods.

Read 11 tweets
DAIR.AI Profile picture
Aug 4, 2024
The Top ML Papers of the Week (July 29 - August 4):

- MindSearch
- Refusal in LLMs
- Constrained-CoT
- Meta-Rewarding LLMs
- Evaluating Persona Agents
- Improved RAG with Self-Reasoning
...
1/ Meta-Rewarding LLMs - proposes a self-improving alignment technique (no human supervision) where the LLM judges its own judgements and uses the feedback to improve its judgment skills...

2/ MindSearch - presents an LLM-based multi-agent framework to perform complex web-information seeking and integration tasks; a web planner effectively decomposes complex queries followed by a web searcher that performs hierarchical information retrieval on the Internet to improve the relevancy of the retrieved information.

Read 11 tweets
DAIR.AI Profile picture
May 26, 2024
The Top ML Papers of the Week (May 20 - May 26):

- Guide for Evaluating LLMs
- Efficient Multimodal LLMs
- Scientific Applications of LLMs
- Enhancing Answer Selection in LLMs
- Claude 3 Sonnet Interpretable Features
- Agent Planning with World Knowledge Model
...
1/ Extracting Interpretable Features from Claude 3 - presents an effective method to extract millions of abstract features from an LLM that represent specific concepts; these concepts could represent people, places, programming abstractions, and more...

2/ Agent Planning with World Knowledge Model - a parametric world knowledge model to facilitate agent planning; the agent model can self-synthesize knowledge from expert and sampled trajectories; this is used to train the world knowledge model.

Read 11 tweets
DAIR.AI Profile picture
Mar 31, 2024
The Top ML Papers of the Week (March 25 - March 31):

- DBRX
- Grok-1.5
- LLM2LLM
- Mini-Gemini
- Agent Lumos
- Long-form factuality in LLMs
...
1). DBRX - a new 132B parameter open LLM that outperforms all the established open-source models on common benchmarks like MMLU and GSM8K; DBRX was pretrained on 12T tokens (text and code) and uses a mixture-of-experts (MoE) architecture.

2). Grok-1.5 - xAI’s latest long-context LLM for advanced understanding and reasoning and problem-solving capabilities; Grok-1.5 achieved a 50.6% score on the MATH benchmark and a 90% score on the GSM8K benchmark.

Read 11 tweets
DAIR.AI Profile picture
Feb 25, 2024
The Top ML Papers of the Week (Feb 19 - Feb 25):

- LoRA+
- Gemma
- Stable Diffusion 3
- OpenCodeInterpreter
- Revisiting REINFORCE in RLHF
- CoT Reasoning without Prompting
...
1/ Stable Diffusion 3 - a suite of image generation models ranging from 800M to 8B parameters; combines diffusion transformer architecture and flow matching for improved performance in multi-subject prompts, image quality, and spelling abilities.

2/ Gemma - a series of open models inspired by the same research and tech used for Gemini; includes 2B (trained on 2T tokens) and 7B (trained on 6T tokens) models including base and instruction-tuned versions; trained on a context length of 8192 tokens.

Read 11 tweets

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