<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News - Newest: &#34;diffusion&#34;</title><link>https://news.ycombinator.com/newest</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Wed, 14 Oct 2026 07:14:08 +0000</lastBuildDate><atom:link href="https://hnrss.org/newest?points=100&amp;q=diffusion" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[Can you use autoregressive diffusion to generate market data?]]></title><description><![CDATA[
<p>Article URL: <a href="https://blog.janestreet.com/can-you-use-autoregressive-diffusion-to-generate-market-data/">https://blog.janestreet.com/can-you-use-autoregressive-diffusion-to-generate-market-data/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=50021410">https://news.ycombinator.com/item?id=50021410</a></p>
<p>Points: 186</p>
<p># Comments: 57</p>
]]></description><pubDate>Fri, 09 Oct 2026 14:56:13 +0000</pubDate><link>https://blog.janestreet.com/can-you-use-autoregressive-diffusion-to-generate-market-data/</link><dc:creator>jsomers</dc:creator><comments>https://news.ycombinator.com/item?id=50021410</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=50021410</guid></item><item><title><![CDATA[How to build a diffusion language model]]></title><description><![CDATA[
<p>Article URL: <a href="https://kuleshov-group.github.io/blog/blog/2026/how-to-build-a-diffusion-language-model/">https://kuleshov-group.github.io/blog/blog/2026/how-to-build-a-diffusion-language-model/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=49503956">https://news.ycombinator.com/item?id=49503956</a></p>
<p>Points: 184</p>
<p># Comments: 20</p>
]]></description><pubDate>Sun, 30 Aug 2026 23:41:32 +0000</pubDate><link>https://kuleshov-group.github.io/blog/blog/2026/how-to-build-a-diffusion-language-model/</link><dc:creator>volodia</dc:creator><comments>https://news.ycombinator.com/item?id=49503956</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49503956</guid></item><item><title><![CDATA[Continuous Diffusion Language Models (CDLM's)]]></title><description><![CDATA[
<p>Article URL: <a href="https://sander.ai/2026/08/24/continuous-dlms.html">https://sander.ai/2026/08/24/continuous-dlms.html</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=49502611">https://news.ycombinator.com/item?id=49502611</a></p>
<p>Points: 135</p>
<p># Comments: 48</p>
]]></description><pubDate>Sun, 30 Aug 2026 20:46:53 +0000</pubDate><link>https://sander.ai/2026/08/24/continuous-dlms.html</link><dc:creator>peter_d_sherman</dc:creator><comments>https://news.ycombinator.com/item?id=49502611</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49502611</guid></item><item><title><![CDATA[Learning the Integral of a Diffusion Model]]></title><description><![CDATA[
<p>Article URL: <a href="https://sander.ai/2026/05/06/flow-maps.html">https://sander.ai/2026/05/06/flow-maps.html</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=48040002">https://news.ycombinator.com/item?id=48040002</a></p>
<p>Points: 161</p>
<p># Comments: 23</p>
]]></description><pubDate>Wed, 06 May 2026 18:46:27 +0000</pubDate><link>https://sander.ai/2026/05/06/flow-maps.html</link><dc:creator>benanne</dc:creator><comments>https://news.ycombinator.com/item?id=48040002</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48040002</guid></item><item><title><![CDATA[Introspective Diffusion Language Models]]></title><description><![CDATA[
<p>Article URL: <a href="https://introspective-diffusion.github.io/">https://introspective-diffusion.github.io/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=47762641">https://news.ycombinator.com/item?id=47762641</a></p>
<p>Points: 281</p>
<p># Comments: 55</p>
]]></description><pubDate>Tue, 14 Apr 2026 07:57:33 +0000</pubDate><link>https://introspective-diffusion.github.io/</link><dc:creator>zagwdt</dc:creator><comments>https://news.ycombinator.com/item?id=47762641</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47762641</guid></item><item><title><![CDATA[Hamilton-Jacobi-Bellman Equation: Reinforcement Learning and Diffusion Models]]></title><description><![CDATA[
<p>Article URL: <a href="https://dani2442.github.io/posts/continuous-rl/">https://dani2442.github.io/posts/continuous-rl/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=47571495">https://news.ycombinator.com/item?id=47571495</a></p>
<p>Points: 171</p>
<p># Comments: 53</p>
]]></description><pubDate>Mon, 30 Mar 2026 07:34:04 +0000</pubDate><link>https://dani2442.github.io/posts/continuous-rl/</link><dc:creator>sebzuddas</dc:creator><comments>https://news.ycombinator.com/item?id=47571495</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47571495</guid></item><item><title><![CDATA[From Noise to Image – interactive guide to diffusion]]></title><description><![CDATA[
<p>Article URL: <a href="https://lighthousesoftware.co.uk/projects/from-noise-to-image/">https://lighthousesoftware.co.uk/projects/from-noise-to-image/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=47163167">https://news.ycombinator.com/item?id=47163167</a></p>
<p>Points: 154</p>
<p># Comments: 21</p>
]]></description><pubDate>Thu, 26 Feb 2026 07:52:29 +0000</pubDate><link>https://lighthousesoftware.co.uk/projects/from-noise-to-image/</link><dc:creator>simedw</dc:creator><comments>https://news.ycombinator.com/item?id=47163167</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47163167</guid></item><item><title><![CDATA[Mercury 2: Fast reasoning LLM powered by diffusion]]></title><description><![CDATA[
<p>Article URL: <a href="https://www.inceptionlabs.ai/blog/introducing-mercury-2">https://www.inceptionlabs.ai/blog/introducing-mercury-2</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=47144464">https://news.ycombinator.com/item?id=47144464</a></p>
<p>Points: 351</p>
<p># Comments: 128</p>
]]></description><pubDate>Tue, 24 Feb 2026 22:46:23 +0000</pubDate><link>https://www.inceptionlabs.ai/blog/introducing-mercury-2</link><dc:creator>fittingopposite</dc:creator><comments>https://news.ycombinator.com/item?id=47144464</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47144464</guid></item><item><title><![CDATA[Consistency diffusion language models: Up to 14x faster, no quality loss]]></title><description><![CDATA[
<p>Article URL: <a href="https://www.together.ai/blog/consistency-diffusion-language-models">https://www.together.ai/blog/consistency-diffusion-language-models</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=47083648">https://news.ycombinator.com/item?id=47083648</a></p>
<p>Points: 219</p>
<p># Comments: 96</p>
]]></description><pubDate>Fri, 20 Feb 2026 04:15:58 +0000</pubDate><link>https://www.together.ai/blog/consistency-diffusion-language-models</link><dc:creator>zagwdt</dc:creator><comments>https://news.ycombinator.com/item?id=47083648</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47083648</guid></item><item><title><![CDATA[TurboDiffusion: 100–200× Acceleration for Video Diffusion Models]]></title><description><![CDATA[
<p>Article URL: <a href="https://github.com/thu-ml/TurboDiffusion">https://github.com/thu-ml/TurboDiffusion</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=46388907">https://news.ycombinator.com/item?id=46388907</a></p>
<p>Points: 248</p>
<p># Comments: 46</p>
]]></description><pubDate>Fri, 26 Dec 2025 03:19:49 +0000</pubDate><link>https://github.com/thu-ml/TurboDiffusion</link><dc:creator>meander_water</dc:creator><comments>https://news.ycombinator.com/item?id=46388907</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46388907</guid></item><item><title><![CDATA[Qwen-Image-Layered: transparency and layer aware open diffusion model]]></title><description><![CDATA[
<p>Article URL: <a href="https://huggingface.co/papers/2512.15603">https://huggingface.co/papers/2512.15603</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=46321972">https://news.ycombinator.com/item?id=46321972</a></p>
<p>Points: 130</p>
<p># Comments: 21</p>
]]></description><pubDate>Fri, 19 Dec 2025 03:24:26 +0000</pubDate><link>https://huggingface.co/papers/2512.15603</link><dc:creator>dvrp</dc:creator><comments>https://news.ycombinator.com/item?id=46321972</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46321972</guid></item><item><title><![CDATA[Terrain Diffusion: A Diffusion-Based Successor to Perlin Noise]]></title><description><![CDATA[
<p>Article URL: <a href="https://arxiv.org/abs/2512.08309">https://arxiv.org/abs/2512.08309</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=46221594">https://news.ycombinator.com/item?id=46221594</a></p>
<p>Points: 154</p>
<p># Comments: 42</p>
]]></description><pubDate>Wed, 10 Dec 2025 18:37:27 +0000</pubDate><link>https://arxiv.org/abs/2512.08309</link><dc:creator>kelseyfrog</dc:creator><comments>https://news.ycombinator.com/item?id=46221594</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46221594</guid></item><item><title><![CDATA[Image Diffusion Models Exhibit Emergent Temporal Propagation in Videos]]></title><description><![CDATA[
<p>Article URL: <a href="https://arxiv.org/abs/2511.19936">https://arxiv.org/abs/2511.19936</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=46055177">https://news.ycombinator.com/item?id=46055177</a></p>
<p>Points: 124</p>
<p># Comments: 22</p>
]]></description><pubDate>Wed, 26 Nov 2025 07:55:49 +0000</pubDate><link>https://arxiv.org/abs/2511.19936</link><dc:creator>50kIters</dc:creator><comments>https://news.ycombinator.com/item?id=46055177</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46055177</guid></item><item><title><![CDATA[Multimodal Diffusion Language Models for Thinking-Aware Editing and Generation]]></title><description><![CDATA[
<p>Article URL: <a href="https://github.com/tyfeld/MMaDA-Parallel">https://github.com/tyfeld/MMaDA-Parallel</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=45977542">https://news.ycombinator.com/item?id=45977542</a></p>
<p>Points: 136</p>
<p># Comments: 12</p>
]]></description><pubDate>Wed, 19 Nov 2025 09:27:17 +0000</pubDate><link>https://github.com/tyfeld/MMaDA-Parallel</link><dc:creator>lnyan</dc:creator><comments>https://news.ycombinator.com/item?id=45977542</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=45977542</guid></item><item><title><![CDATA[TiDAR: Think in Diffusion, Talk in Autoregression]]></title><description><![CDATA[
<p>Article URL: <a href="https://arxiv.org/abs/2511.08923">https://arxiv.org/abs/2511.08923</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=45939036">https://news.ycombinator.com/item?id=45939036</a></p>
<p>Points: 130</p>
<p># Comments: 22</p>
]]></description><pubDate>Sat, 15 Nov 2025 17:32:35 +0000</pubDate><link>https://arxiv.org/abs/2511.08923</link><dc:creator>internetguy</dc:creator><comments>https://news.ycombinator.com/item?id=45939036</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=45939036</guid></item><item><title><![CDATA[Show HN: Tiny Diffusion – A character-level text diffusion model from scratch]]></title><description><![CDATA[
<p>This is a character-level language diffusion model for text generation.<p>The model is a modified version of Nanochat's GPT implementation and is trained on Tiny Shakespeare!<p>It is only 10.7 million parameters, so you can try it out locally.</p>
<hr>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=45876742">https://news.ycombinator.com/item?id=45876742</a></p>
<p>Points: 172</p>
<p># Comments: 20</p>
]]></description><pubDate>Mon, 10 Nov 2025 15:13:55 +0000</pubDate><link>https://github.com/nathan-barry/tiny-diffusion</link><dc:creator>nathan-barry</dc:creator><comments>https://news.ycombinator.com/item?id=45876742</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=45876742</guid></item><item><title><![CDATA[The Principles of Diffusion Models]]></title><description><![CDATA[
<p>Article URL: <a href="https://arxiv.org/abs/2510.21890">https://arxiv.org/abs/2510.21890</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=45866572">https://news.ycombinator.com/item?id=45866572</a></p>
<p>Points: 239</p>
<p># Comments: 31</p>
]]></description><pubDate>Sun, 09 Nov 2025 16:10:23 +0000</pubDate><link>https://arxiv.org/abs/2510.21890</link><dc:creator>Anon84</dc:creator><comments>https://news.ycombinator.com/item?id=45866572</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=45866572</guid></item><item><title><![CDATA[BERT is just a single text diffusion step]]></title><description><![CDATA[
<p>Article URL: <a href="https://nathan.rs/posts/roberta-diffusion/">https://nathan.rs/posts/roberta-diffusion/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=45644328">https://news.ycombinator.com/item?id=45644328</a></p>
<p>Points: 455</p>
<p># Comments: 110</p>
]]></description><pubDate>Mon, 20 Oct 2025 14:31:16 +0000</pubDate><link>https://nathan.rs/posts/roberta-diffusion/</link><dc:creator>nathan-barry</dc:creator><comments>https://news.ycombinator.com/item?id=45644328</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=45644328</guid></item><item><title><![CDATA[Diffusion language models are super data learners]]></title><description><![CDATA[
<p>Article URL: <a href="https://jinjieni.notion.site/Diffusion-Language-Models-are-Super-Data-Learners-239d8f03a866800ab196e49928c019ac">https://jinjieni.notion.site/Diffusion-Language-Models-are-Super-Data-Learners-239d8f03a866800ab196e49928c019ac</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=44856101">https://news.ycombinator.com/item?id=44856101</a></p>
<p>Points: 218</p>
<p># Comments: 16</p>
]]></description><pubDate>Sun, 10 Aug 2025 16:04:05 +0000</pubDate><link>https://jinjieni.notion.site/Diffusion-Language-Models-are-Super-Data-Learners-239d8f03a866800ab196e49928c019ac</link><dc:creator>babelfish</dc:creator><comments>https://news.ycombinator.com/item?id=44856101</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=44856101</guid></item><item><title><![CDATA[Hacking Diffusion into Qwen3 for the Arc Challenge]]></title><description><![CDATA[
<p>Article URL: <a href="https://www.matthewnewton.com/blog/arc-challenge-diffusion">https://www.matthewnewton.com/blog/arc-challenge-diffusion</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=44798624">https://news.ycombinator.com/item?id=44798624</a></p>
<p>Points: 126</p>
<p># Comments: 23</p>
]]></description><pubDate>Tue, 05 Aug 2025 14:43:12 +0000</pubDate><link>https://www.matthewnewton.com/blog/arc-challenge-diffusion</link><dc:creator>mattnewton</dc:creator><comments>https://news.ycombinator.com/item?id=44798624</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=44798624</guid></item></channel></rss>