🎓How I Study AIHISA
📖Read
📄Papers📰Blogs🎬Courses
💡Learn
🛤️Paths📚Topics💡Concepts🎴Shorts
🎯Practice
🧩Problems🎯Prompts🧠Review
Search
How I Study AI - Learn AI Papers & Lectures the Easy Way

Papers784

AllBeginnerIntermediateAdvanced
All SourcesarXiv

Shaping capabilities with token-level data filtering

Intermediate
Neil Rathi, Alec RadfordJan 29arXiv

The paper shows a simple way to teach AI models what not to learn by removing only the exact words (tokens) related to unwanted topics during pretraining.

#token-level data filtering#capability shaping#sparse autoencoders

ASTRA: Automated Synthesis of agentic Trajectories and Reinforcement Arenas

Intermediate
Xiaoyu Tian, Haotian Wang et al.Jan 29arXiv

ASTRA is a fully automated way to train tool-using AI agents by making both their practice stories (trajectories) and their practice worlds (environments) without humans in the loop.

#tool-augmented agents#multi-turn decision making#verifiable environments

MemOCR: Layout-Aware Visual Memory for Efficient Long-Horizon Reasoning

Intermediate
Yaorui Shi, Shugui Liu et al.Jan 29arXiv

MemOCR is a new way for AI to remember long histories by turning important notes into a picture with big, bold parts for key facts and tiny parts for details.

#MemOCR#visual memory#adaptive information density

Latent Chain-of-Thought as Planning: Decoupling Reasoning from Verbalization

Intermediate
Jiecong Wang, Hao Peng et al.Jan 29arXiv

This paper introduces PLaT, a way for AI to think silently in a hidden space (the brain) and only speak when needed (the mouth).

#latent chain-of-thought#planning in latent space#planner-decoder architecture

Self-Improving Pretraining: using post-trained models to pretrain better models

Intermediate
Ellen Xiaoqing Tan, Shehzaad Dhuliawala et al.Jan 29arXiv

This paper teaches language models to be safer, more factual, and higher quality during pretraining, not just after, by using reinforcement learning with a stronger model as a helper.

#self-improving pretraining#reinforcement learning#online DPO

Qwen3-ASR Technical Report

Intermediate
Xian Shi, Xiong Wang et al.Jan 29arXiv

Qwen3‑ASR is a family of speech models that hear, understand, and write down speech in 52 languages and dialects, plus they can tell you when each word was spoken.

#ASR#forced alignment#timestamps

Grounding and Enhancing Informativeness and Utility in Dataset Distillation

Intermediate
Shaobo Wang, Yantai Yang et al.Jan 29arXiv

This paper tackles dataset distillation by giving a clear, math-backed way to keep only the most useful bits of data, so models can learn well from far fewer images.

#dataset distillation#data condensation#Shapley value

Scaling Embeddings Outperforms Scaling Experts in Language Models

Intermediate
Hong Liu, Jiaqi Zhang et al.Jan 29arXiv

The paper shows that growing the embedding part of a language model (especially with n-grams) can beat adding more MoE experts once you pass a certain sparsity 'sweet spot.'

#N-gram Embedding#Mixture-of-Experts (MoE)#Embedding Scaling

Do Reasoning Models Enhance Embedding Models?

Intermediate
Wun Yu Chan, Shaojin Chen et al.Jan 29arXiv

The paper asks a simple question: if a language model becomes better at step-by-step reasoning (using RLVR), do its text embeddings also get better? The short answer is no.

#text embeddings#RLVR#contrastive learning

MAD: Modality-Adaptive Decoding for Mitigating Cross-Modal Hallucinations in Multimodal Large Language Models

Intermediate
Sangyun Chung, Se Yeon Kim et al.Jan 29arXiv

Multimodal AI models can mix up what they see and what they hear, making things up across senses; this is called cross-modal hallucination.

#multimodal large language models#cross-modal hallucination#contrastive decoding

CUA-Skill: Develop Skills for Computer Using Agent

Intermediate
Tianyi Chen, Yinheng Li et al.Jan 28arXiv

This paper builds a big, reusable library of computer skills so an AI can use Windows apps more like a careful human, not a clumsy robot.

#computer-using agents#desktop automation#skill library

Thinking in Frames: How Visual Context and Test-Time Scaling Empower Video Reasoning

Intermediate
Chengzu Li, Zanyi Wang et al.Jan 28arXiv

This paper shows that making short videos can help AI plan and reason in pictures better than writing out steps in text.

#video reasoning#visual planning#test-time scaling
1314151617