Large language models are increasingly regarded as strong translators, yet it remains unclear what their success establishes beyond overall translation quality. This question is especially consequential in Chinese web novel translation, where sentence-level cultural meaning shapes tone, characterization, and reader experience. Existing evaluation provides only indirect evidence, as benchmarks emphasize overall quality and available metrics do not explicitly assess the cultural and pragmatic phenomena underlying reader experience. We introduce DITING (a mythological creature known for discerning truth), the first comprehensive evaluation framework for this problem, supported by an expert-annotated benchmark of over 18K Chinese-English sentence pairs, a reasoning-driven multi-agent evaluator, AgentEval, and a 1,440-pair meta-evaluation benchmark, MetricAlign. AgentEval achieves the strongest correlation with human judgments among eight representative automatic metrics. Applying DITING to 14 translation systems shows that current progress is selective rather than general: frontier LLMs lead overall, but their gains concentrate in a subset of dimensions, while zero-pronoun resolution remains the clearest bottleneck. Overall, our results show that aggregate rankings substantially overstate how broadly sentence-level cultural meaning has been solved in web novel translation. All the code and data in https://github.com/whunextgen/DITING.

Large Language Models (LLMs) can play a vital role in psychotherapy by adeptly handling the crucial task of cognitive reframing and overcoming challenges such as shame, distrust, therapist skill variability, and resource scarcity. Previous LLMs in cognitive reframing mainly converted negative emotions to positive ones, but these approaches have limited efficacy, often not promoting clients’ self-discovery of alternative perspectives. In this paper, we unveil the Helping and Empowering through Adaptive Language in Mental Enhancement (HealMe) model. This novel cognitive reframing therapy method effectively addresses deep-rooted negative thoughts and fosters rational, balanced perspectives. Diverging from traditional LLM methods, HealMe employs empathetic dialogue based on psychotherapeutic frameworks. It systematically guides clients through distinguishing circumstances from feelings, brainstorming alternative viewpoints, and developing empathetic, actionable suggestions. Moreover, we adopt the first comprehensive and expertly crafted psychological evaluation metrics, specifically designed to rigorously assess the performance of cognitive reframing, in both AI-simulated dialogues and real-world therapeutic conversations. Experimental results show that our model outperforms others in terms of empathy, guidance, and logical coherence, demonstrating its effectiveness and potential positive impact on psychotherapy.