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5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.8 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 VoiceCodeBench arXiv paper proposes benchmark for exact structured-token recovery in speech recognition — 1 src1.4 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.8 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 VoiceCodeBench arXiv paper proposes benchmark for exact structured-token recovery in speech recognition — 1 src1.4 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src
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#conversational-ai

5 curated events
papersTODAY 04:00 UTC

arXiv Paper Examines How Users Mistreat Conversational AI Systems

A new arXiv preprint studies how users direct hostility, coercion, and adversarial pressure at conversational AI models, an area the authors say is often overlooked in favor of research on model-generated harms. The paper argues that understanding when and why such mistreatment happens is needed to correctly interpret model behavior and alignment drift. It appears under the cs.AI category as a new submission.

safety/alignment/conversational-ai/user-behavior
papersSEP 10 04:00 UTC

RESCUE-BENCH: A Benchmark for Relation-Aware Multi-Party Emotional Support Conversations

Researchers have introduced RESCUE-BENCH, a benchmark designed to push emotional support conversation systems beyond traditional one-on-one interactions. The work addresses the gap in handling multi-party scenarios, where the relationships between participants shape how support should be delivered. It marks a step toward support systems that reason about interpersonal dynamics rather than just individual emotional states.

benchmark/conversational-ai/emotional-support/multi-party
papersSEP 10 04:00 UTC

Paper documents shift from monolithic model to agentic orchestration in support assistant

An arXiv paper describes how a large accommodation marketplace migrated its production customer-support assistant away from a single blended model pipeline. The new architecture separates retrieval, action selection, escalation, and response wording into orchestrated agentic components chosen dynamically per request. The authors report on deployment at scale and the practical lessons learned during the transition.

agents/conversational-ai/customer-support/case-study
papersSEP 10 04:00 UTC

EviMem proposes evidence-gap-driven iterative retrieval for long-term conversational memory

Researchers present EviMem, a retrieval method for long-term conversational memory that identifies gaps in the evidence gathered so far and iteratively fetches additional material across past sessions. The approach targets temporal and multi-hop questions where a single retrieval pass typically fails to locate relevant information. The paper is available as a revised version (v2) on arXiv.

retrieval/memory/conversational-ai/research
papersSEP 12 04:00 UTC

Ablation Study Examines Which Speech Cues Drive End-of-Turn Detection

A new arXiv paper investigates how much different aspects of speech contribute to detecting when a speaker has finished their turn in a conversation. The authors run a controlled ablation of a conversational system to separate the relative weight of each modality, noting that the role of semantics versus other cues is still poorly understood. The work targets more natural turn-taking in conversational AI.

speech/turn-taking/conversational-ai/research