Why Alignment Shapes LLM Behavior More Than Personality
Apologies, refusals, and sycophancy in LLMs are shaped more by alignment, rewards, and prompting than personality.
Humanoids, autonomy, and embodied AI.
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Apologies, refusals, and sycophancy in LLMs are shaped more by alignment, rewards, and prompting than personality.
MKGR combines one sequence modality and four knowledge graphs to improve cold-start PPI prediction over prior baselines.
As multiple-choice medical benchmarks saturate, open-ended clinical reasoning and safety are becoming key measures.
Why scientific ML paper reproduction needs workflow, progress tracking, and evidence-claim matching beyond code generation.
ZCode highlights a shift from code completion to long-running agent workflows with persistent context in AI development tools.
A curated link roundup from recently collected official updates and tech news.
A summary of arXiv 2607.01793 on automating agent safety testing from risk discovery to evidence-grounded verification.
A paper on combining RLVR with human demonstrations to train style, structure, and diversity beyond verifiable rewards.
Code model evaluation should weigh real task success, retries, latency, and token cost, not benchmark scores alone.
How CoAx exposes backup circuits that single ablation can miss due to self-repair in transformers.
How ContextNest frames context governance with a verifiable knowledge vault layer for auditable AI agents beyond retrieval quality.
A look at RL research using latent space to generate counterfactual feedback in StarCraft II and its coaching potential.
DiscoLoop explores multi-hop reasoning inside a single forward pass without relying on long external CoT tokens.
Examines whether combining rail crossing images with accident records improves safety assessment and what validation matters.
OCB evaluates native Office file understanding, revealing document AI limits beyond PDF-based QA.
Reviewing where AI and quantum information already deliver practical gains, and why quantum ML advantage still needs caution.
AI can boost productivity but also amplify errors, making foundational learning essential for problem framing, verification, and judgment.
AI data center risks hinge less on hype than on grid connection, cooling design, water tracking, and permitting.
A curated link roundup from recently collected official updates and tech news.
How code agents can use bug reproduction tests as diagnostic signals during patch generation, not just post-hoc checks.
DART-VLN targets stale memory reads and local backtracking in discrete VLN using training-free test-time control.
A method for building dynamic 3D Gaussians from monocular video and correcting reconstruction gaps with a conditional video model.
From steering vectors to model calibrators, this paper frames latent-space intervention as a path to better LLM control and trust.
Examines why remote robots on NTN need memory-based communication that uses past link states and task context.