References: Reasoning over multimodal inputs

Source material

Source material:
• Stanford CS25 V5 (May 6, 2025):
  "Reasoning Models as Agents: Deliberative Alignment, Multimodal Intelligence,
   and Tool Use"
  Speaker: Hongyu Ren (OpenAI, Member of Technical Staff; led o-mini series)
  Course event page: https://ee-www.stanford.edu/event/05-06-2025/reasoning-models-agents-deliberative-alignment-multimodal-intelligence-and-tool
  YouTube: not publicly available at draft time
  License (when posted): as published on Stanford's public CS25 YouTube channel
                        (link-out only)

PENDING-RECORDING NOTE (transparent attribution): at the time of this lesson's
drafting (2026-05-25), Hongyu Ren's V5 L6 lecture was over a year past Stanford
CS25's typical 2-week recording-publication window, and no YouTube recording
surfaced through public search of the official Stanford CS25 channel, the CS25
recordings page, or related searches. This may indicate the recording was not
published (some speakers do not authorize public release) rather than being in
the publication window; the situation differs from a freshly-delivered lecture
awaiting publication.

The lesson is structured around the three topics the lecture title names
(reasoning extended to multimodal inputs, tool use, deliberative alignment),
grounded on the publicly-available OpenAI deliberative-alignment paper and the
publicly-documented o-series reasoning-model literature, rather than on
specific claims attributed to Ren's lecture. Per the pending-recording pattern
ratified 2026-05-25, the Lead's promotion sweep will resolve the URL situation:
if a recording is eventually located or posted, it is wired to source_material.
primary_url at promotion; if confirmed unpublished, the Lead may decide whether
to leave the lesson with the type:youtube/no-primary_url pattern or substitute
a different source attribution.

Clawdemy provides original notes, summaries, and quizzes derived from publicly
available material for educational purposes. All rights to Ren's lecture remain
with Stanford and the speaker.

What this lesson draws from

This lesson is the structural-mirror counterpart to Ren’s V5 L6 lecture on the topics of multimodal reasoning, tool use, and deliberative alignment. The substantive technical content draws on the publicly-published OpenAI deliberative-alignment writeup and paper, the public o-series reasoning-model literature, and the publicly-documented behavior of modern multimodal reasoning systems, rather than on specific claims attributed to Ren’s lecture (per the pending-recording pattern’s line-2 constraint: category-membership only, not content claims).

The four-layer architecture stack framing (perception + reasoning + tool use + alignment), the failure-layer diagnostic, and the explicit deferral of broader agent-philosophy to lesson 9 are Clawdemy’s own connective tissue.

Going deeper

• “Deliberative Alignment: Reasoning Enables Safer Language Models” (OpenAI, 2024). The paper introducing deliberative alignment as the alignment technique behind OpenAI’s o-series. Section 2 is the core mechanism (training the model to reason explicitly over a written safety specification).
• OpenAI’s deliberative-alignment writeup. The more accessible public announcement of the same work, with results figures and intuitive explanations.
• Stanford CS25 V5 schedule. For readers who want the full V5 lineup; useful context for where Ren’s lecture sat in the series.

Adjacent topics

• The o-series and successor reasoning models. A growing family across labs (OpenAI o-series, Google’s thinking modes, Anthropic’s extended thinking). The capability pattern recurs; the underlying mechanism is the inference-time compute described here.
• Multimodal agents in production (lesson 9). This lesson stops at per-query multimodal reasoning; lesson 9 picks up the broader agent design (RL co-design with product, multimodal tool use in shipped systems) that the V5 L2 Karina Nguyen lecture covers.
• Adversarial multimodal attack surfaces. Prompts in images, adversarial visual content, jailbreaks via the visual channel. An active research area; deliberative alignment helps but does not solve. Outside this track’s scope; worth knowing exists.

Community discussion

None selected for this lesson at draft time. The OpenAI deliberative-alignment paper and writeup together are the strongest public reading; if Ren’s recording surfaces or a canonical thread appears, it will be added at the next review.