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9 results for "ai optimization"

ARXIV.ORG

CAP-CoT: Cycle Adversarial Prompt for Improving Chain of Thoughts in LLM Reasoning

Chain-of-Thought (CoT) prompting has emerged as a simple and effective way to elicit step-by-step solutions from large language models (LLMs). However, CoT reasoning can be unstable across runs on lon…

· 3 views
ARXIV.ORG

Escher-Loop: Mutual Evolution by Closed-Loop Self-Referential Optimization

While recent autonomous agents demonstrate impressive capabilities, they predominantly rely on manually scripted workflows and handcrafted heuristics, inherently limiting their potential for open-ende…

· 3 views
FIRETHERING

Xiaomi releases MiMo-v2.5 Family weights with strong coding and agent benchmarks

Peking University gives its computer science students a compiler project every semester. Build a complete SysY compiler in Rust including lexer, parser, abstract syntax tree, IR code generation, assem…

· 2 views
ARXIV.ORG

Discovering Agentic Safety Specifications from 1-Bit Danger Signals

Can large language model agents discover hidden safety objectives through experience alone? We introduce EPO-Safe (Experiential Prompt Optimization for Safe Agents), a framework where an LLM iterative…

· 2 views
ARXIV.ORG

Agentic Adversarial Rewriting Exposes Architectural Vulnerabilities in Black-Box NLP Pipelines

Multi-component natural language processing (NLP) pipelines are increasingly deployed for high-stakes decisions, yet no existing adversarial method can test their robustness under realistic conditions…

· 3 views
ARXIV.ORG

A2DEPT: Large Language Model-Driven Automated Algorithm Design via Evolutionary Program Trees

Designing heuristics for combinatorial optimization problems (COPs) is a fundamental yet challenging task that traditionally requires extensive domain expertise. Recently, Large Language Model (LLM)-b…

· 2 views
ARXIV.ORG

Explanation Quality Assessment as Ranking with Listwise Rewards

We reformulate explanation quality assessment as a ranking problem rather than a generation problem. Instead of optimizing models to produce a single "best" explanation token-by-token, we train reward…

· 2 views
ARXIV.ORG

Certified geometric robustness -- Super-DeepG

Safety-critical applications are required to perform as expected in normal operations. Image processing functions are often required to be insensitive to small geometric perturbations such as rotation…

· 2 views
REDDIT

Intel B70: LLama.ccp SYCL vs LLama.cpp OpenVino vs LLM-Scaler

In case anyone is interested, I decided to test out LLama.cpp's new OpenVino backend to see how it compares on Intel GPUs. At first glance, it stomps all over the previous best-case, SYCL, but lags be…

· 6 views