Computer Science Conference Impact Factors

20252026

Venue impact scores for 2025–2026, plus the topics researchers wrote about most in recent conference titles — and what to learn next for 2027.

How selective vs how impactful?

Each bubble is one conference.

Read it like this: up = higher impact score; left = more selective (lower acceptance %).
Right = higher acceptance (easier to get in). Bigger bubble = more papers in 2024–2025. Color = field.
Strong venues often sit high and toward the left: selective + highly cited.

Selectiveness (→) vs Impact (↑) — bubble size = paper volume

AI Systems Theory Interdisciplinary

Most written topic & subtopics

Built from ~3.7k publication titles in 2024–2025 proceedings (DBLP). Bars = how often the phrase family appears in titles.

Highest-scoring venues (easy ranking)

Top 12 conferences by 2026 impact score, with 2025 shown beside it.

Longer bar = higher score. Compare blue (2025) vs orange (2026) to see year-to-year movement.
2025 score 2026 score

Topics to learn for 2027

A practical study roadmap from title momentum (what the community is publishing now) projected one year ahead.

Upcoming conference deadlines

From mlciv AI Deadlines (ML, CV, CG, NLP, RO, SP, DM, AP, KR, HCI, EDU). Times shown in each conference’s listed timezone.

Conference Year Deadline Countdown Place Conference dates Subjects

Latest 2026 resources for trending topics

Curated courses, docs, guides, and paper hubs matched to the hottest title themes (agents, multimodal, efficiency, safety, robotics, biomedical).

Conference metrics table

Click headers to sort. Search by conference, field, or topic.

Conference IF 2025 IF 2026 Median cites Papers 2024–25 Acceptance % Field Top title topics

Methodology (2025–2026 update)

What we measure, how scores are built, and how topics are extracted.

  1. Venue set. Conferences from CSRankings / CORE A* style lists (same family as the original csimpact study).
  2. Impact score. For each venue we blend: (a) prior Google-Scholar-style impact factor, (b) OpenAlex 2-year mean citedness when available, (c) recent publication volume from DBLP (2024–2025). Separate IF 2025 / IF 2026 values weight each year’s paper share and topic momentum.
  3. Most-written topics. We sample paper titles from DBLP for each venue, then count phrase families (e.g., “large language model”, “diffusion”, “LoRA”). Parent topics and finer subtopics are ranked by title mentions.
  4. Topics to learn for 2027 + 2026 resources. We take the strongest title signals from 2024–2026 momentum and pair them with current courses, docs, and paper hubs.
  5. Conference deadlines. Upcoming submission deadlines are imported from mlciv AI Deadlines for ML/CV/CG/NLP/RO/SP/DM/AP/KR/HCI/EDU (refresh with update-deadlines.ps1).

Sources: DBLP, OpenAlex, original method arXiv:2310.08037. These are research analytics estimates, not Clarivate Journal Citation Reports.