…AI can help read literature, generate hypotheses, and plan protocols, yet the execution of those protocols at the bench still requires a human operator. Vision-Language-Action (VLA) models provide one possible…
…However, existing methods either learn a topology that remains fixed at inference time or adapt only the topology or capability during inference. We empirically and theoretically show that effective test-time evolution…
…DeltaRubric operates in two steps: acting first as a Disagreement Planner , the model generates a neutral, instance-specific verification checklist. Transitioning into a Checklist Verifier , it executes these self-generated checks against…
…Counterfactual Unlearning for Large Reasoning Models through Iterative Preference Optimization (2026) Before Forgetting, Learn to Remember: Revisiting Foundational Learning Failures in LVLM Unlearning Benchmarks (2026) Please give a thumbs up to this…
…Importance-Weighted Fine-Tuning), a framework that operationalizes the theoretical insight that the KL-regularized RL objective is equivalent to importance-weighted supervised learning . DRIFT decouples rollout from optimization by sampling offline…
…A Case Study Comparing Experts, Students, Crowdworkers, and Large Language Model (2026) Do We Still Need Humans in the Loop? Comparing Human and LLM Annotation in Active Learning for Hostility Detection (2026…
…Ziyu Guo , , , Abstract ATLAS presents a visual reasoning framework that combines agentic operations and latent representations using functional tokens, enabling efficient training and improved performance on complex benchmarks. AI-generated summary Visual…
…operations into compact procedural rules reusable across projects. A memory module maintains user- and project-specific experience that grounds planning decisions in each user's research history. A label-free policy learning…
…Eliciting General Reasoning in LLMs with Reinforcement Learning on Natural Instructions (2026) Learning to Generate Formally Verifiable Step-by-Step Logic Reasoning via Structured Formal Intermediaries (2026) Apriel-1.5-OpenReasoner: RL…
…Diversity in Evolutionary Inference , a distributed Quality-Diversity (QD) search framework that assigns heterogeneous large language models (LLMs) as mutation operators across peer nodes communicating with non-blocking collective operations . Unlike homogeneous…