Planner
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Related Articles from SNS
Wedding dreams in tatters as dozens of brides told their Tenerife wedding planner has gone bust
Wedding dreams in tatters as dozens of brides told their Tenerife wedding planner has gone bust On Friday, around 20 couples were suddenly sent an email informing them that the business that is planning their wedding is now bankrupt, leaving their dream nuptials in tatters Dozens of brides have had their dreams of a perfect wedding day in Tenerife ruined after being told their wedding planner's business has gone bust. Some of the brides say they had handed over as much as £30,000 to the...
Royal wedding rerun as Peter Phillip marriage organised by same planner as his original
Royal wedding rerun as Peter Phillip marriage organised by same planner as his original Peter Phillips is set to marry NHS nurse Harriet Sperling in an 'intimate' Cotswolds ceremony - with King Charles, Queen Camilla and many senior royals expected to attend Peter Phillips is set to tie the knot for the second time next week - and is using the same wedding planner as his first time around. The 48-year-old nephew to the King is due to marry NHS nurse Harriet Sperling in the Cotswolds next...
Planner-Centric Reinforcement Learning for Deep Research with Structure-Aware Reward
Announce Type: new Abstract: Deep research tasks require LLMs to plan what to investigate, retrieve evidence, and synthesize long-form answers across multiple branches of inquiry. Existing training paradigms either rely on short-form verifiable QA as a proxy or optimize monolithic long trajectories, which makes planning and execution difficult to disentangle and yields weak credit assignment for the planning process. We propose DecomposeR, a planner-centric deep research framework that...
Improving Diffusion Planners by Self-Supervised Action Gating with Energies
arXiv:2603.02650v2 Announce Type: replace Abstract: Diffusion planners are a strong approach for offline reinforcement learning, but they can fail when value-guided selection favours trajectories that score well yet are locally inconsistent with the environment dynamics, resulting in brittle execution. We propose Self-supervised Action Gating with Energies (SAGE), an inference-time re-ranking method that penalises dynamically inconsistent plans using a latent consistency signal. SAGE trains...
LAP: Fast LAtent Diffusion Planner for Autonomous Driving
arXiv:2512.00470v4 Announce Type: replace Abstract: Diffusion models have demonstrated strong capabilities for modeling human-like driving behaviors in autonomous driving, but their iterative sampling process induces substantial latency, and operating directly on raw trajectory points forces the model to spend capacity on low-level kinematics, rather than high-level multi-modal semantics. To address these limitations, we propose LAtent Planner (LAP), a framework that plans in a VAE-learned...
Correct Is Not Enough: Training Reasoning Planners with Executor-Grounded Rewards
arXiv:2605.03862v4 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards has become a common way to improve explicit reasoning in large language models, but final-answer correctness alone does not reveal whether the reasoning trace is faithful, reliable, or useful to the model that consumes it. This outcome-only signal can reinforce traces that are right for the wrong reasons, overstate reasoning gains by rewarding shortcuts, and propagate flawed intermediate states...
CodeGraphVLP: Code-as-Planner Meets Semantic-Graph State for Non-Markovian Vision-Language-Action Models
arXiv:2604.22238v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models promise generalist robot manipulation, but are typically trained and deployed as short-horizon policies that assume the latest observation is sufficient for action reasoning. This assumption breaks in non-Markovian long-horizon tasks, where task-relevant evidence can be occluded or appear only earlier in the trajectory, and where clutter and distractors make fine-grained visual grounding brittle. We...
FF-JEPA: Long-Horizon Planning in World Models with Latent Planners
Announce Type: new Abstract: Joint Embedding Predictive Architectures (JEPAs) have shown promising world modeling capabilities, enabling planning in latent space by optimizing action trajectories using methods like the Cross-Entropy Method (CEM). These methods are, however, too computationally expensive and ineffective for long-horizon planning. Furthermore, these methods typically require an explicit image of the goal state, which is not always possible in real-world tasks.
Token Predictors Are Not Planners: Building Physically Grounded Causal Reasoners
Announce Type: new Abstract: Current benchmarks for embodied vision-language planning often favor linguistic next-token prediction over physically grounded next-state reasoning. This rewards models that mimic statistical language priors rather than track causal dependencies, reducing physical planning to shallow sequence modeling. We argue that reliable physical autonomy requires a shift from linguistically grounded token prediction toward physically grounded causal reasoning.
Mrs Dalloway review – Virginia Woolf’s party planner plays all the roles herself
Storyhouse, ChesterKit Green takes on all the characters in an imaginative interpretation of the 1925 day-in-the-life novelAs Clarissa Dalloway wafts about the stage, welcoming her audience indiscriminately before instigating party games, the essence of Virginia Woolf’s scrupulous socialite appears to be missing. But this stage adaptation – co-written by Jen Heyes, who directs, and Kit Green, who performs – is a playful re-examination of the novel, wrapped up as a multimedia-driven solo...