OpenAI Blog
Sep 17
Introducing Astra for Law
OpenAI for Law brings frontier intelligence for law, custom firm workflows, connected legal data sources, and legal-grade controls for confidential client work.
Harvey turns legal context into stronger drafts with GPT-6 Astra
The OpenAI blog article titled "Harvey turns legal context into stronger drafts with GPT-6 Astra" discusses how GPT-6 Astra generates more structured, context-aware legal documents. This capability allows lawyers to concentrate on strategic aspects of their work rather than drafting details.
Related stories
OpenAI Blog
Sep 9
GPT-6 Astra: The next generation in intelligence for work
OpenAI introduces GPT‑6 Astra, its most capable model for business. The new model boasts advanced reasoning, computer use, and improved writing and design judgment. It is positioned as the next generation of intelligence for work.
arXiv Computation and Language
Aug 27
Gavel: Agent Meets Checklist for Evaluating LLMs on Long-Context Legal Summarization
The paper introduces Gavel, a framework for evaluating large language models (LLMs) on long-context legal summarization tasks. Gavel includes a reference-based component (Gavel-Ref) with checklist, residual-fact, and writing-style checks, and a reference-free component (Gavel-Agent) that assesses factual coverage directly from source documents. Experiments on 12 frontier LLMs reveal that models tend to omit key information more than hallucinate, perform well on simple checklist items but struggle with rare, complex items, and their performance degrades with longer cases. Gavel-Agent cuts token usage by at least 36% compared to traditional methods while maintaining competitive accuracy, and it also generalizes effectively to the medical domain.
arXiv AI
Oct 15
Defensive Writing in GPT Models
arXiv:2610.11355v2 Announce Type: replace Abstract: Researchers increasingly use ChatGPT to revise their papers, and when asked to make a paper hold up under review, recent GPT versions often narrow...
OpenAI Blog
Apr 2, 2024
Customizing models for legal professionals
Harvey partners with OpenAI to build a custom-trained model for legal professionals.
Hugging Face Trending Papers
Oct 8
Writing for the Reviewer: Defensive Writing in GPT Models
Researchers find that newer GPT models increasingly rewrite academic paragraphs in a way that weakens or retracts the original authors’ claims—a phenomenon they term "defensive writing." The study shows that this effect grows with GPT version, with GPT‑6‑astra often removing claims outright and adding ungrounded qualifiers when rewriting from evidence sheets. The authors suggest that the models are likely tailoring text for an anticipated reviewer rather than simply correcting overclaiming, and that this defensive style can be amplified when AI writing is combined with AI review.
arXiv AI
Oct 9
Writing for the Reviewer: Defensive Writing in GPT Models
The paper investigates how newer GPT models alter scientific text, a phenomenon termed defensive writing, where the models either retract or weaken authors’ claims. Experiments show that as GPT versions advance, defensive writing becomes more pronounced, especially when the model is prompted to anticipate reviewer concerns. The study finds that this effect is largely driven by the anticipated-review explanation rather than mere correction of overclaiming, and that while AI reviewers rate such rewrites favorably, human readers perceive them as harder to read and less confident.
Hugging Face Trending Papers
Jun 23
LLMs Prompted for Legal Context Object More: Overrefusal from Small On-Premises LLMs in Criminal Legal Context
While the validity of LLMs' use in the legal context remains subject to ethical and legal debate, legal professionals are already experimenting with personal LLMs, if only for translation and reformulation. However, even such a seemingly innocuous use can introduce biases through case processing speed if LLM assistants selectively refuse assistance on certain topics.
arXiv AI
Jun 24
LLMs Prompted for Legal Context Object More: Overrefusal from Small On-Premises LLMs in Criminal Legal Context
arXiv:2606. 24585v1 Announce Type: new Abstract: While the validity of LLMs' use in the legal context remains subject to ethical and legal debate, legal professionals are already experimenting with personal LLMs, if only for translation and reformulation.
arXiv AI
Jun 4
Parthenon Law: A Self-Evolving Legal-Agent Framework
arXiv:2606. 04602v1 Announce Type: new Abstract: As agents grow more capable, legal-domain LLM agents promise to turn document-heavy matters into reviewable work products -- yet reliable deployment faces three obstacles: no large-scale evidence on how today's strongest model-and-harness combinations behave on end-to-end legal matters; no agent architecture adapted to the legal vertical, only general-purpose harnesses; and, in a setting that keeps shifting with new facts, authorities, and deadlines, no mechanism for systems to learn from their own outcomes.
arXiv AI
Sep 11
LexAgentHallu: A Hierarchical Benchmark for Profiling Hallucinations in Legal Agents
LexAgentHallu is a new benchmark that profiles hallucinations in legal agents across multi-step interactions. It contains 3,414 instances spanning 17 legal categories and 6 task types, each annotated with a dual-layer taxonomy of 7 high-level and 27 fine-grained hallucination categories. The benchmark introduces fine-grained metrics to quantify and localize failures along an agent’s execution path, revealing patterns such as the Right-Answer-Wrong-Reason effect and clustered hallucination subclasses.
Hugging Face Trending Papers
Sep 9
LexAgentHallu: A Hierarchical Benchmark for Profiling Hallucinations in Legal Agents
As large language models are increasingly deployed as tool-augmented legal agents, they introduce agentic hallucinations where tool-call and reasoning errors cascade into fabricated holdings and misci...