Notable data and AI papers

Papers627Labs45

627 papers · 45 labs

dLLM: Simple Diffusion Language Modeling research paper by UC Berkeley, 2026

UC Berkeley · Foundation models · Feb 26, 2026 · 18 citations · 136 upvotes · unverified

Read on arXiv

What it shows

A unified open-source framework is presented that standardizes core components of diffusion language modeling for reproduction, customization, and accessible development of both large and small models.

By Zhanhui Zhou, Lingjie Chen, Hanghang Tong and 1 more · arXiv 2602.22661 · PDF · Code

UnverifiedHugging Face's summary; not yet checked by hand.

More from UC Berkeley

All 14
ArchitecturesUnverifiedOct 14, 2026Correction Training for Diffusion ModelsThis method adds a correction step to diffusion models to fix errors that accumulate during the image generation process.UC Berkeley42 upvotesRead →Multimodal and roboticsUnverifiedSep 29, 2026OmniTaskonomy: When Does Visual Generation Improve Visual Understanding?This paper maps how visual generation tasks improve visual understanding capabilities, revealing specific task-dependent transfer benefits.UC Berkeley57 upvotesRead →Inference and efficiencyUnverifiedAug 17, 2026FreeToken: Efficient Edge-Native MoE Serving with Bandwidth-Adaptive ExecutionFreeToken is an edge-native Mixture-of-Experts serving system that dynamically maps computation and model state onto heterogeneous local hardware to run large open-weight models on personal machines.UC Berkeley8 citations86 upvotesRead →Agents and evaluationUnverifiedJun 17, 2026Playful Agentic Robot LearningEmbodied robots learn reusable skills through self-directed play and exploration, then apply these skills to improve performance on downstream tasks without additional training.UC Berkeley37 citations49 upvotesRead →Agents and evaluationJun 3, 2026Agents' Last ExamOver 1,000 real, checkable professional tasks written with 250+ industry experts; the hardest tier is far from solved.UC Berkeley42 citations393 upvotesRead →Inference and efficiencyUnverifiedMar 10, 2026Flash-KMeans: Fast and Memory-Efficient Exact K-MeansFlash-kmeans enables efficient online k-means clustering on GPUs through novel kernel-level optimizations that eliminate I/O bottlenecks and reduce atomic write contention.UC Berkeley16 citations64 upvotesRead →Inference and efficiencyUnverifiedFeb 13, 2026SLA2: Sparse-Linear Attention with Learnable Routing and QATSLA2 improves sparse-linear attention in diffusion models by introducing a learnable router, direct attention formulation, and quantization-aware fine-tuning for enhanced efficiency and quality.UC Berkeley1 citations59 upvotesRead →Inference and efficiencyUnverifiedFeb 3, 2026Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache QuantizationQuant VideoGen addresses KV cache memory limitations in autoregressive video diffusion models through semantic-aware smoothing and progressive residual quantization, achieving significant memory reduction with minimal latency impact.UC Berkeley29 citations35 upvotesRead →

Other foundation models papers

Topic
Foundation modelsOct 11, 2018BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingPre-training a Transformer to fill in masked words, then fine-tuning it, beat task-specific models across language understanding tests.Google125k citations33 upvotesRead →Foundation modelsMay 28, 2020Language Models are Few-Shot LearnersGPT-3, a 175B-parameter model, does new tasks from a few examples in the prompt, with no fine-tuning.OpenAI66.4k citations21 upvotesRead →Foundation modelsMar 15, 2023GPT-4 Technical ReportA multimodal model that passes a simulated bar exam with a score around the top 10% of test takers.OpenAI28.4k citations7 upvotesRead →Foundation modelsFeb 27, 2023LLaMA: Open and Efficient Foundation Language ModelsOpen models from 7B to 65B trained only on public data; the 13B model beats GPT-3 on most benchmarks.Meta22.6k citations25 upvotesRead →Foundation modelsJul 31, 2024The Llama 3 Herd of ModelsOpen models up to 405B parameters that match leading closed models on many tasks.Meta20.8k citations119 upvotesRead →Foundation modelsUnverifiedMay 14, 2025Qwen3 Technical ReportQwen3, a unified series of large language models, integrates thinking and non-thinking modes, reduces computational resources, and achieves state-of-the-art performance across various tasks and languages.Alibaba (Qwen)10.1k citations339 upvotesRead →
About this paper
Venue
Annual Meeting of the Association for Computational Linguistics
Citations
18, 1 influential · Semantic Scholar
Upvotes
136 · Hugging Face
Lab
UC Berkeley

Changes

UpvotesNov 9, 2026Hugging Face upvotes fell from 153 to 136.
CitationsNov 9, 2026Citations rose from 17 to 18.
CitationsNov 2, 2026Citations rose from 15 to 17.
CitationsOct 12, 2026Citations rose from 14 to 15.
CitationsOct 5, 2026Citations rose from 12 to 14.
CitationsSep 25, 2026A first count of 1 influential citations.
CitationsSep 25, 2026A first count of 12 citations.
New paperSep 25, 2026Found by the weekly Hugging Face scan; not yet checked by hand.