Built with and by Teycir Ben Soltane•
How to Use•FAQ•GitHub•arXiv.org•
Share:
Index Stats4,350 papers
ArXivCSExplorer

Understand any CS paper in 60 seconds — no login required

Hybrid search: keyword + semanticⓘ| Semantic-only search →

Try: LoRA fine-tuning·ZK-SNARKs·distributed consensus·Mamba SSM

All Features

Everything you need to explore, understand, and track CS research

📝

Abstract Search

Paste any paper text to find semantically similar work instantly

⚖️

Compare

Side-by-side diff of two papers — methods, results, claims

🌐

Explore

Browse the full indexed arXiv CS corpus

👤

Authors

Researcher profiles, timelines and co-author graphs

★

Bookmarks

Save and organise papers for later reading

🔬

Claim Tracker

Type any claim — see which papers support or contradict it

Achievements

View all
0papers
0day streak
0/0badges
First Steps0 / 1

Start reading papers to earn your first badge

Live RSS Feed

Subscribesee all →
cs.CLcs.AI3d ago

Learning to Reason by Analogy via Retrieval-Augmented Reinforcement Fine-Tuning

This paper proposes a post-training framework called Retrieval-Augmented Reinforcement Fine-Tuning (RA-RFT) to teach language models to reason by analogy.

Zilin Xiao, Qi Ma, Chun-cheng Jason Chen et al.

cs.ROcs.AI3d ago

Mana: Dexterous Manipulation of Articulated Tools

This paper presents Mana, a sim-to-real framework for dexterous articulated tool manipulation.

Zhao-Heng Yin, Guanya Shi, Pieter Abbeel et al.

cs.CVcs.AI3d ago

SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning

This paper proposes SpatialClaw, a training-free framework for spatial reasoning that enables open-ended, complex 3D/4D spatial reasoning.

Seokju Cho, Ryo Hachiuma, Abhishek Badki et al.

cs.AI3d ago

Automated reproducibility assessments in the social and behavioral sciences using large language models

This paper shows that large language models can automate reproducibility assessments in the social and behavioral sciences.

Tobias Holtdirk, Pietro Marcolongo, Anna Steinberg Schulten et al.

Recommended for you

From your bookmarks →