SkillFuzz: Fuzzing Skill Composition for Implicit Intents Discovery in Open Skill Marketplaces
SkillFuzz detects implicit intents when composed LLM agent skills in marketplaces redirect execution toward unintended objectives.
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SkillFuzz detects implicit intents when composed LLM agent skills in marketplaces redirect execution toward unintended objectives.
Self-gating attention mechanism reduces quadratic complexity of transformers in time series forecasting via redundant attention map pruning.
SelectTSL combines sound source localization with multimodal prompts for selective target sound direction estimation in complex acoustic scenes.
Certify-then-Rectify framework adds correctness guarantees to HNSW vector search via distribution-free statistical certification without sacrificing speed.
Frameworks like Lean Six Sigma and business process management (BPM) first gained traction because they promised clarity in the chaos—a structured way to bring order to messy, sprawling operations. Lean Six Sigma emphasized statistical rigor and quality control; BPM created…
Pipeline automating physics research from arXiv corpus to publication via LLM agents with external literature grounding to reduce hallucination.
OpenAI CEO Sam Altman has reportedly proposed giving 5% of the company’s equity to a U.S. sovereign wealth fund, reviving discussions about letting the public share in the financial gains from the AI boom.
CCG-based parser with directional type system improves structural generalization on SLOG benchmark, outperforming AM-Parser baseline.
HOLA augments linear-attention models with bounded exact KV cache inspired by complementary learning systems to improve long-range needle recall.
Insiders say Sam Altman is in active talks with the Trump administration.
Applies reinforcement learning perspective to optimize neural quantum state parameterizations via gradient geometry, bridging Adam and stochastic reconfiguration methods.
Distribution-wise reward framework for fine-tuning generative models reduces mode collapse and reward hacking versus sample-wise approaches.
Proves offline RL generalization in CMDPs depends on pessimism structure respecting solution symmetries, not magnitude of conservatism.
Single-layer spiking neural network enables in-context learning via dendritic computation, achieving Garg-2022 benchmark with biological plausibility.
AnyGroundBench evaluates vision-language models on specialized-domain video grounding with rare concepts, revealing domain adaptation gaps beyond zero-shot benchmarks.
HERMES hierarchical labeling substrate using learned semantic transform and residual quantization enables flexible multi-granularity data mixture grouping for pre-training.
CheckRLM detects and corrects factual inconsistencies in reasoning chains via retrieval-augmented claim checking during LLM inference.
BamiBERT improves Vietnamese BERT pretraining with 2048-token context and raw-text support, outperforming PhoBERT on 11/15 benchmarks.
AgenticSTS introduces bounded-memory architecture for LLM agents with typed retrieval instead of transcript accumulation for long-horizon tasks.
Theoretical proof that aggregation with exponential weights achieves minimax-optimal excess risk in expectation for model selection.
Copewell deploys multi-agent swarm for mental wellness support in low-resource settings with dynamic emotional state calibration.
FTC urged to reject Elon Musk’s bid to end X monitoring amid AI concerns.
Paul Bakaus on Impeccable discusses skill engineering, human-in-the-loop agent design, and limitations of one-shot prompting approaches.
Survey identifies limitations of LLM-as-a-Judge evaluation in multilingual and low-resource language settings with inadequate validation.
Purified OPSD fixes on-policy self-distillation failures on long chain-of-thought by decomposing teacher supervision signals.
Confidence-guided classification model for AI-assisted household waste sorting across German municipalities using human-in-the-loop.
CoFL-S predicts language-conditioned flow fields for low-level robot navigation actions in vision-language environments.
SpeechCombine enables speech language models to follow instructions without explicit instruction tuning via text-speech knowledge transfer.
MLP-GNN framework isolates chemical and structural contributions to aqueous solubility predictions for drug discovery.
Guard Rail Validation framework standardizes runtime interception and validation of AI agent decisions in autonomous telecom networks before execution.