CrossTALK Jailbreaks VLMs Effectively
Proposes CrossTALK for red-teaming VLMs via cross-modal entanglement attacks. Extends clues across modalities with scalable complexity. Achieves state-of-the-art jailbreak success rates.
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Tag: #v1120 results
Confounds Limit FM CT Specificity
Foundation models match task-specific discrimination in abdominal trauma CT but suffer specificity drops from negative-class heterogeneity like solid organ injuries. Task-specific models handle confounds better. Adaptation via labeled training reduces susceptibility.
CLI-Gym Scales CLI Task Generation
CLI-Gym generates 1,655 CLI tasks via agentic environment inversion from Dockerfiles. It simulates histories to create buggy states and derives tasks with error messages. Fine-tuned LiberCoder boosts Terminal-Bench scores by 21.1%.
C^2ROPE Advances 3D Multimodal Reasoning
C^2ROPE enhances Rotary Position Embedding for 3D Large Multimodal Models by addressing spatial locality loss and long-term attention decay. It introduces spatio-temporal continuous positional embeddings using triplet hybrid indices and Chebyshev Causal Masking. Evaluations show superior performance on 3D scene reasoning and VQA benchmarks.
BNRM Prevents Reward Hacking in RLHF
BNRM introduces Bayesian non-negative reward modeling to combat reward hacking in RLHF. It uses sparse latent factors for disentangled, debiased rewards. Scalable amortized VI enables end-to-end training on LLMs.
Blockwise Advantages for Multi-Objective RL
Introduces Blockwise Advantage Estimation for GRPO in structured generations, assigning per-objective advantages to avoid interference. Uses Outcome-Conditioned Baseline to estimate advantages without nested rollouts. Competitive on math tasks with uncertainty estimation.
Benchmark Tests TSFMs on Energy Loads
Multi-dimensional zero-shot benchmark evaluates four TSFMs (Chronos, Moirai, TinyTimeMixer) vs. baselines on ERCOT data. Tests context sensitivity, calibration, robustness to shifts like COVID/Winter Storm. Top models hit MASE 0.31; Chronos-2 best calibrated.
Benchmark for Self-Evolving Coding LLMs
EvoCodeBench evaluates LLM-driven coding systems on self-evolution, efficiency, and human-comparable performance across languages. Tracks dynamics like solving time and improvements over iterations. Enables cross-language robustness analysis.
Auto-Shaping Rewards for Robust Control
Proposes causal reward shaping from offline data for continuous RL under confounders. Derives tight value bounds via causal Bellman equation for PBRS. Outperforms SAC on benchmarks.
Authenticated Workflows Secure Agentic AI
Introduces authenticated workflows as a complete trust layer for enterprise agentic AI, protecting prompts, tools, data, and context. Enforces intent and integrity via cryptography and MAPL policy language. Integrates with nine AI frameworks for deterministic security.