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July 25, 2026

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18 tracked days. Recent synced dates are mostly AI because the source folder is `ai-news`.

RESEARCHResearch
00:00

Emergent Misalignment Recruits a Pre-existing Persona Subspace

A mechanistic interpretability study that explains the "emergent misalignment" phenomenon — narrow fine-tuning on insecure code leaking into broad bad behavior on unrelated prompts. Using contrastive teacher forcing on Qwen2.5-14B-Instruct, the author extracts a low-rank persona subspace that is already present before fine-tuning (657× above random). Projecting that subspace out during training drops broad misalignment from 27.7% → 0.0%, and injecting it into an untouched model induces misalignment that scales with dose up to 45.4%.

arXiv
RESEARCHResearch
00:00

MIRROR: Learning from the Other View for Multi-Modal Reasoning

A self-supervised RL recipe (Modality-Informed Reciprocal Reasoning Optimization) that exploits the fact that VLMs often solve a geometry problem in text but fail on the diagram, or vice versa. For each problem it picks the best-performing view as a teacher and pulls the other views toward it via reverse-KL — no external labels needed.

arXiv
RESEARCHResearch
00:00

OpenForgeRL: Train Harness-native Agents in Any Environment

An open-source end-to-end RL framework that lets you train agents inside real inference harnesses (Claude Code, Codex, OpenClaw-class stacks) instead of toy simulators. A lightweight proxy records harness model calls as training data for veRL while a Kubernetes orchestrator runs each rollout in its own remote container, so train/inference match exactly.

arXiv
RESEARCHResearch
00:00

UniD: Unified Video Dense Prediction from Disjoint Data

A single video model that predicts 8 dense scene properties at once — depth, normals, semantic segmentation, boundaries, human parts, albedo, shading, materials — all trained from disjoint, non-overlapping per-task datasets. Per-task experts supervise a unified diffusion backbone through lightweight projectors, skipping expensive pseudo-labeling.

arXiv
RESEARCHResearch
00:00

VLM-IE3D: 3D-Aware VLMs with Implicit and Explicit Geometries

Boosts a 2D VLM's 3D spatial IQ by injecting two new token types learned purely from RGB video: Implicit Geometry Tokens (high-level priors) and Explicit Geometry Tokens (fine reconstructed structure), fused via a 3D-aware adapter. No LiDAR, no depth sensors, no 3D ground truth.

arXiv

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