RSEA adds a strict held-out keep-better gate to recursive self-evolution of agent artifacts, yielding monotone-safe gains or parity with the base ReAct agent on ALFWorld, GAIA, τ-bench, and WebShop.
Does tone change the answer? evaluating prompt politeness effects on modern LLMs: GPT, Gemini, LLaMA
7 Pith papers cite this work. Polarity classification is still indexing.
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About 18.2% of structurally flagged skill pairs represent genuine compositional safety risks in agent skill registries, with exploitation gated by host model behavior.
TOPD improves on-policy distillation for LLM reasoning by using near-future guidance to identify divergent states, raising average accuracy from 47.8% to 52.2% on math benchmarks including AIME24 and AIME25.
PPM derives a tractable gradient for exact KL optimization in diffusion variational inversion to achieve unbiased posterior matching without heuristic approximations.
ConsisVLA-4D adds cross-view semantic alignment, cross-object geometric fusion, and cross-scene dynamic reasoning to VLA models, delivering 21.6% and 41.5% gains plus 2.3x and 2.4x speedups on LIBERO and real-world tasks.
Toxic prompt perturbations reduce LLM factual accuracy on three benchmarks and selectively amplify perturbation-sensitive nodes in attribution graphs.
Reflect-Guard fine-tunes Llama-Guard-3-8B with distilled self-reflections to raise F1 on WildGuardTest from 0.770 to 0.842 and cut JailbreakBench attack success from 10.3% to 1.8%.
citing papers explorer
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Recursive Self-Evolving Agents via Held-Out Selection
RSEA adds a strict held-out keep-better gate to recursive self-evolution of agent artifacts, yielding monotone-safe gains or parity with the base ReAct agent on ALFWorld, GAIA, τ-bench, and WebShop.
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When Safe Skills Collide: Measuring Compositional Risk in Agent Skill Ecosystems
About 18.2% of structurally flagged skill pairs represent genuine compositional safety risks in agent skill registries, with exploitation gated by host model behavior.
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Bridging Reasoning Trajectories in On-Policy Distillation via Near-Future Guidance
TOPD improves on-policy distillation for LLM reasoning by using near-future guidance to identify divergent states, raising average accuracy from 47.8% to 52.2% on math benchmarks including AIME24 and AIME25.
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Unbiased Diffusion Variational Inversion via Principled Posterior Matching
PPM derives a tractable gradient for exact KL optimization in diffusion variational inversion to achieve unbiased posterior matching without heuristic approximations.
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ConsisVLA-4D: Advancing Spatiotemporal Consistency in Efficient 3D-Perception and 4D-Reasoning for Robotic Manipulation
ConsisVLA-4D adds cross-view semantic alignment, cross-object geometric fusion, and cross-scene dynamic reasoning to VLA models, delivering 21.6% and 41.5% gains plus 2.3x and 2.4x speedups on LIBERO and real-world tasks.
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Toxic HallucinAItions: Perturbing Prompts and Tracing LLM Circuits
Toxic prompt perturbations reduce LLM factual accuracy on three benchmarks and selectively amplify perturbation-sensitive nodes in attribution graphs.
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Reflect-Guard: Enhancing LLM Safeguards against Adversarial Prompts via Logical Self-Reflection
Reflect-Guard fine-tunes Llama-Guard-3-8B with distilled self-reflections to raise F1 on WildGuardTest from 0.770 to 0.842 and cut JailbreakBench attack success from 10.3% to 1.8%.